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Economic Bulletin December 2016

Lisbon, 2016 • www.bportugal.pt

Economic Bulletin | December 2016 • Banco de Portugal Rua do Comércio, 148 | 1100-150 Lisboa • www.bportugal.pt

• Edition Economics and Research Department • Design and printing Communication Directorate | Image and Graphic

Design Unit • Print run 25 • ISSN 0872-9794 (print) • ISSN 2182-0368 (online) • Legal Deposit no. 241772/06

ContentsI Projections for the Portuguese economy: 2016-19

Box 1 | Projection assumptions | 13

Box 2 | Impact of uncertainty measures on the Portuguese economy | 29

II Special issue

Life below zero: monetary policy transmission under negative interest rates | 37

IProjections for the Portuguese economy: 2016-19

Box 1 | Projection assumptions

Box 2 | Impact of uncertainty measures on the Portuguese economy

7Projections for the Portuguese economy: 2016-19

Projections for the Portuguese economy: 2016-19

1. IntroductionOver the projection horizon, the Portuguese economy is expected to maintain the moder-ate recovery trajectory that has characterised recent years (Table 1.1). Thus, following 1.2 per cent growth in 2016, gross domestic product (GDP) is projected to accelerate to 1.4 per cent in 2017, stabilising its growth rate at 1.5 per cent for the following years. This implies that at the end of the projection horizon, GDP will reach a level identical to that recorded in 2008. In the period 2017-19, GDP growth is expected

to be close to, albeit lower than, that projected for the euro area, not reverting the negative differential accumulated between 2010 and 2013 (Chart 1.1). This lack of real convergence with the euro area reflects persisting structural constraints to the growth of the Portuguese economy, in which high levels of public and pri-vate sector indebtedness, unfavourable demo-graphic developments and persisting inefficien-cies in the employment and product markets play an important role, requiring the deepening of the structural reform process.

Table 1.1 • Projections of Banco de Portugal for 2016-19 | Annual rate of change, in percentage

Weights 2015

2015

EB December 2016EB October

2016EB June 2016

2016(p) 2017(p) 2018(p) 2019(p) 2016(p) 2016(p) 2017(p) 2018(p)

Gross domestic product 100.0 1.6 1.2 1.4 1.5 1.5 1.1 1.3 1.6 1.5

Private consumption 65.6 2.6 2.1 1.3 1.4 1.3 1.8 2.1 1.7 1.3

Public consumption 18.2 0.8 1.0 0.0 0.4 0.2 1.0 1.1 0.4 0.6

Gross fixed capital formation 15.3 4.5 -1.7 4.4 4.3 4.5 -1.8 0.1 4.3 4.6

Domestic demand 99.3 2.5 1.2 1.5 1.7 1.6 1.1 1.8 1.7 1.7

Exports 40.6 6.1 3.7 4.8 4.6 4.4 3.0 1.6 4.7 4.7

Imports 39.8 8.2 3.5 4.8 4.9 4.4 3.0 2.8 4.9 4.8

Contribution to GDP growth net of imports (in p.p.) (a)

Domestic demand 1.1 0.4 0.5 0.6 0.6 0.5 1.0 0.7 0.7

Exports 0.5 0.8 0.9 0.8 0.9 0.6 0.3 0.9 0.9

Employment (b) 1.4 1.5 1.0 0.9 1.0 1.0 – – –

Unemployment rate 12.4 11.0 10.1 9.4 8.5 11.2 – – –

Current plus capital account (% of GDP) 1.7 1.1 0.9 0.9 1.1 1.3 1.9 1.6 1.6

Trade balance (% of GDP) 1.8 2.2 1.9 1.8 1.8 2.1 1.6 1.3 1.2

Harmonized index of consumer prices 0.5 0.8 1.4 1.5 1.5 0.7 0.7 1.4 1.5

Sources: Statistics Portugal and Banco de Portugal.Notes: (p) –projected, (p.p.) – percentage points. For each aggregate, this table shows the projection corresponding to the most likely value, conditional on the set of assumptions considered. (a) The demand aggregates net of imports are obtained by subtracting an estimate of the imports needed to meet each component. For more information, see the Box entitled ‘The role of domestic demand and exports in economic activity developments in Portugal’, in the June 2014 issue of the Economic Bulletin. (b) Total employment, in number of persons according to the national accounts concept.

BANCO DE PORTUGAL • Economic Bulletin • December 20168

This projection is part of the Eurosystem’s pro-

jection exercise recently published by the Euro-

pean Central Bank (ECB). According to this exer-

cise assumptions, the Portuguese economy’s

external environment should remain favourable,

albeit with a downward revision of international

trade flows in comparison to previous exercises

(Box ‘Projection assumptions’). Following a slack-

ening in 2016, external demand should accel-

erate over the projection horizon, even though

more slowly than that observed prior to the

international financial crisis. Furthermore, mon-

etary and financial conditions are expected to

remain generally accommodative. In turn, over

the projection horizon, energy and non-ener-

gy commodity prices should reverse the down-

ward trajectory observed in recent years.

Against this generally favourable background,

exports of goods and services should be more

dynamic than external demand, as observed in

recent years. Therefore, exports will continue

to be the overall demand component with the

greatest contribution to economic growth. The

greater buoyancy of the Portuguese economy

vis-à-vis 2016 will be underpinned by an accelera-

tion in gross fixed capital formation (GFCF), based

on a recovery of business investment. In turn,

private consumption should decelerate com-pared to that observed over the last few years, growing in line with potential output expecta-tions. The strong momentum in consumption in recent years is associated with expenditure on durable goods, resulting in part from purchasing decisions delayed during the 2011-13 recession.

Developments in activity should be accompanied by the gradual recovery of the labour market situation, with continued employment growth, despite the progressively more moderate pace, and the continued downward path of the unem-ployment rate.

Inflation measured by the Harmonised Index of Consumer Prices (HICP) should increase over the projection horizon, remaining at levels close to the euro area average. The acceleration of prices – to about 1.5 per cent at the end of the horizon – reflects domestic and external up-ward pressures.

Over the projection horizon, the Portuguese economy is expected to maintain an external net lending position, albeit at lower levels than in recent years. This profile is determined by devel-opments in the income and capital accounts. The trade balance as a percentage of GDP, fol-lowing a temporary increase in 2016, will remain

Chart 1.1 • GDP | In

percentage and index

(2008=100)

-5.0

-3.0

-1.0

1.0

3.0

5.0

90

95

100

105

110

2008 2010 2012 2014 2016 (p) 2018 (p)

Annual rate of change Portugal (rhs) Annual rate of change euro area (rhs)Index (2008=100) Portugal Index (2008=100) euro area

Sources: Statistics Portugal, ECB and Banco de Portugal.

Note: (p) – projected.


relatively unchanged compared to 2015 for the rest of the projection horizon.

Thus the economic growth pattern projected – in which exports and GFCF are the components presenting a dynamism above that of GDP – is compatible with a more sustained recovery of the Portuguese economy, especially in a situ-ation in which external net lending is main-tained and additional reductions in private sec-tor indebtedness are projected.

2. Recent Information The projections for the Portuguese economy pre-sented in this Bulletin include the information set available until 24 November 2016 and the tech-nical assumptions underlying the Eurosystem’s projection exercise, recently released by the ECB (Box ‘Projection assumptions’).

In the first half of 2016, GDP grew moderately at 0.9 per cent in year-on-year terms, prolonging the deceleration that started in the second half of 2015. In comparison with the previous semes-ter, economic activity increased by 0.5 per cent.

The slackening of activity in year-on-year terms was the result of smaller positive contributions from domestic demand and exports, as observed in the second half of 2015. Weaker buoyancy in domestic demand in year-on-year terms essen-tially reflected the fall in investment, with a reduc-tion in GFCF of 2.7 per cent in the first half of 2016 (+4.5 per cent in 2015). Developments in this aggregate are largely explained by the falls of GFCF in construction and in machin-ery and equipment, as investment in transport equipment maintained robust growth, albeit lower than in the second half of 2015. In turn, more moderate export growth in the first half of 2016 reflected the negative developments of fuel exports, whose import content is quite sig-nificant (about 95 per cent). To a lesser extent, there was also a reduction in services exports excluding tourism.

Considering the aggregates net of imports (i.e. deducting from each demand component an estimate for the imports necessary to meet that demand), it is estimated that GDP developments

in the first half of 2016 are associated with a decel-eration in domestic demand, as export growth net of imported components stabilised versus the preceding six month period (Chart 2.1).

In a context of further improvement in terms of trade, and notwithstanding the stronger volume growth in imports than in exports, the trade bal-ance surplus as a percentage of GDP increased in comparison to the first half of 2015. Howev-er, the current plus capital account surplus fell,1

reflecting the increase in the primary income account deficit and the fall in the balances of the secondary income and capital accounts.

In the first half of 2016, the labour market con-tinued to improve, with a reduction in the unem-ployment rate (of -1.2 percentage points (p.p.) compared to the same period of 2015) and an increase in total employment (quarterly nation-al accounts concept) of 0.9 per cent in year-on-year terms (Chart 2.2).

Strong acceleration of economic activity in the third quarter of 2016

In the third quarter of 2016, according to the flash estimate released by Statistics Portugal (Instituto Nacional de Estatística – INE), GDP in-creased by 1.6 per cent in year-on-year terms, growing by 0.8 per cent on quarter-on-quarter terms (Chart 2.3).

The breakdown of GDP into its main expendi-ture components was only released after the cut-off date for this Bulletin. Therefore, the analysis of GDP aggregates in the third quarter of 2016 is based on recent short-term indicators and the qualitative information contained in the flash esti-mate press release.

Thus, the acceleration in economic activity, in year-on-year terms, was driven by an acceler-ation in exports and a slightly higher growth in domestic demand. In turn, the strong growth compared to the second quarter of 2016 reflect-ed the positive contribution of exports of goods and services, in contrast to the negative contri-bution made by domestic demand.


Stronger growth of private consumption and further decline in investment

Against a background of real disposable income growth, declining unemployment rate and par-ticularly high levels of consumer confidence, it is estimated that private consumption has grown sharply, more than the GDP growth rate observed in the third quarter. The acceleration of this aggregate in year-on-year terms has essen-tially reflected the acceleration of non-durable consumption, visible in the marked increase in the deflated retail turnover index and ATM with-drawals and payments. On the other hand, there was a deceleration in expenditure in consum-er durables for the second consecutive quar-ter, explained by the slowdown in purchases of light passenger vehicles (note that this item grew strongly in the first quarter of this year, largely reflecting purchases brought forward due to the increase in the Tax on Vehicles with the entry into force of the State budget for 2016 at the beginning of April). The strong growth of this aggregate in recent years has to be seen against

a background of the recovery of the passen-ger car stock following the particularly expres-sive declines accumulated throughout the recent recession in the Portuguese economy.

In contrast, GFCF is estimated to have regis-tered a fall in year-on-year terms, albeit less marked than in the two previous quarters. Developments in GFCF continued to reflect the decline in the construction component, in line with developments in cement sales, condi-tioned by the marked fall in public investment. In terms of investment in machinery and equip-ment, short-term indicators available, in par-ticular nominal imports of this type of goods, point to an increase in the third quarter, after the falls observed in the previous three quar-ters (Chart 2.4). The weakness of this compo-nent of GFCF in the second half of 2015 and the beginning of 2016 likely reflected postponed investment decisions, against a background of heightened domestic and international uncer-tainty (Box ‘Impact of uncertainty measures on the Portuguese economy’), combined with a level of capacity utilisation that remains below the historical average. Furthermore, the lower

Chart 2.1 • Net contributions to GDP growth, in year-on-year terms | In percentage points

Chart 2.2 • Employment and unemployment rate | Levels in thousand persons and in percentage of the labour force

-6.0-5.0-4.0-3.0-2.0-1.00.01.02.03.0

2008

H1

2008

H2

2009

H1

2009

H2

2010

H1

2010

H2

2011

H1

2011

H2

2012

H1

2012

H2

2013

H1

2013

H2

2014

H1

2014

H2

2015

H1

2015

H2

2016

H1

Domestic demand Exports GDP (%)

12.4 13.415.0

16.6 17.115.7

14.613.5 12.9 12.3 11.7

0

5

10

15

20

4200

4300

4400

4500

4600

4700

4800

4900

2011

H1

2011

H2

2012

H1

2012

H2

2013

H1

2013

H2

2014

H1

2014

H2

2015

H1

2015

H2

2016

H1

Employment Unemployment rate (rhs)

Sources: Statistics Portugal and Banco de Portugal calculations.

Note: The demand aggregates net of imports are obtained by subtracting an estimate of the imports needed to meet each component. The calculation of import contents was based on data for 2005. For more information, see the Box entitled ‘The role of domestic demand and exports in economic activity develo-pments in Portugal’, in the June 2014 issue of the Economic Bulletin.

Source: Statistics Portugal (QNA and Monthly Employment and Unemploy-ment Estimates).

Note: The unemployment rate data (15 to 74 years old) is seasonally adjusted.


distribution rate of European funds in the first

half of the year, possibly reflecting the tran-

sition to a new National Strategic Reference

Framework (NSRF), may also have conditioned

developments in this variable. Finally, GFCF in

transport equipment decelerated, reflecting less

positive developments in sales of heavy com-

mercial vehicles, as well as a base effect associ-

ated with the import of aeroplanes in the same

quarter of 2015.

Acceleration of exportsIn the third quarter of 2016, the volume of

exports is expected to have presented a quite

buoyant growth rate in year-on-year terms,

exceeding that of the previous quarter and the

estimate for external demand. The acceleration

of exports was common to the goods and ser-

vices components, with emphasis on the strong

increase in exports of goods excluding fuel and

the recovery of services exports excluding tour-

ism. Tourism exports remained quite buoy-

ant, growing at a rate similar to that observed

in previous quarters, against a background of

especially robust growth in recent years. Note

that developments in goods exports in the third

quarter were partially affected by the delivery of

military equipment sold by Portugal to Romania.

However, this operation had a practically neutral

impact on GDP, given that the positive effect on

exports was offset by a negative effect in public

investment in machinery and equipment.

Considering data for the international trade in

goods in nominal terms, there was an accelera-

tion in the third quarter, in year-on-year terms,

in goods exports excluding fuel. Regarding the

developments by country of destination, there

was resilience in exports to European Union (EU)

countries, whose contribution to total export

growth has remained high. Particularly notewor-

thy in the third quarter is the buoyancy of sales

to Spain. In turn, the contribution of exports to

countries outside the EU was substantially less

negative during this period, reflecting a small-

er fall in exports to Angola and a rebound in

exports to Brazil and China (Chart 2.5).

In what concerns the recovery in exports of servic-

es excluding tourism, the nominal information for

Chart 2.3 • Gross domestic product | Real rate of change, in percentage

Chart 2.4 • GFCF in machinery and equipment, in real terms | Year-on-year rate of change, in percentage

-4

-3

-2

-1

0

1

2

2013

Q1

2013

Q3

2014

Q1

2014

Q3

2015

Q1

2015

Q3

2016

Q1

2016

Q3

2013

Q1

2013

Q3

2014

Q1

2014

Q3

2015

Q1

2015

Q3

2016

Q1

2016

Q3

Quarter-on-quarter change Year-on-year change

-12.9

3.713.9

6.0

-20-15-10

-505

10152025

2012 Q1 2013 Q1 2014 Q1 2015 Q1 2016 Q1

Indicator for imports of machinery, in nominal termsGFCF in machinery and equipmentGFCF in machinery and equipment, annual rate of change

Source: Statistics Portugal. Sources: Statistics Portugal and Banco de Portugal.


the third quarter of the services account balance

shows a smaller fall in year-on-year terms in the item passenger transport by air (-1.8 per cent, following -10.4 per cent in the first half of 2016) (Chart 2.6). Furthermore, following weak devel-opments in the second quarter, improvements were registered in exports of telecommunica-tions and IT services and in exports of other ser-vices related to advertising and market research activities and to trade.

Finally, the volume of imports is expected to have accelerated in year-on-year terms in the third quarter. These developments stem from an underlying acceleration in imports of goods (reflecting developments in expenditure aggre-gates with high import content, namely GFCF in machinery and equipment) and tourism, and a recovery of imports of other services. The increase in imports during this period is estimated to have been higher than import-content weighted final demand, leading to a more marked year-on-year increase in the level of import penetration than in the previous quarter.

In the fourth quarter, GDP is expected to con-tinue growing at the same rate in year-on-year terms. This profile is estimated to reflect

an acceleration in private consumption and a smaller decline in GFCF, offset by a deceleration in exports, notwithstanding the impact on tour-ism exports of an important international event held in Lisbon.

With regard to quarter-on-quarter develop-ments, considering that growth in the third quarter partially reflected factors of a tempo-rary nature – with emphasis on the dynamism of goods exports to certain destinations,2 as well as the carrying out of investment decisions postponed in previous quarters – the pace of growth is expected to weaken in the last quar-ter of 2016 to levels close to those observed in the first half of the year.

Chart 2.5 • Nominal exports of goods excluding fuel by country of destination | Contributions to the year-on-year rate of change, in percentage points

Chart 2.6 • Nominal exports of services | Contributions to the year-on-year rate of change, in percentage points

-6

-4

-2

0

2

4

6

8

2013 2014 2015 2016(a)

2015Q4

2016Q1

2016Q2

2016Q3

Intra-EU AngolaBrazil ChinaOther extra-EU countries Total (%)

-8-6-4-202468

1012

2013 2014 2015 2016 (a)

2015 Q4

2016 Q1

2016 Q2

2016 Q3

Travel TransportOther services Total (%)

Source: Statistics Portugal (International Trade Statistics).

Note: (a) Until September.

Source: Banco de Portugal.

Note: (a) Until September.

Projections for the Portuguese economy: 2016-19 13

Box 1 | Projection assumptions

The projections in this Bulletin are based on a set of assumptions regarding the Portuguese

economy’s external environment. These assumptions reflect the information underlying the

Eurosystem’s most recent projections, released on 8 December. The main technical assumptions

are contained in Table 1 and are based on information available up to 24 November.

With regard to the international environment, the current assumptions point to a gradual acce-

leration of world activity and trade over the projection horizon. Despite these positive develop-

ments, global economic growth over the projection horizon is assumed to remain below the ave-

rage recorded prior to the financial crisis. In this context, it is expected that the external demand

directed at the Portuguese economy will grow more in 2017 (3.4 per cent, following 2.0 per cent

in 2016) – but below the average growth rate of 7 per cent observed in the period from 1995 to

2007 – remaining relatively stable at about 4 per cent in 2018 and 2019. The acceleration com-

pared to 2016, common to the intra and extra euro area markets, is more marked in the latter

case, where the fall had been greater. Nevertheless, euro area import demand should continue

to grow more robustly than that of the remainder economies. Considering the assumptions of

previous projection exercises, the external demand for Portuguese goods and services has been

revised downwards over the projection period.

Considering the path implied by futures markets at the cut-off date, it is estimated that, in annual

average terms, oil prices (in dollars and euros) will fall in 2016 vis-à-vis the previous year, conti-

nuing a trend observed since 2013. This falling trend should be interrupted in 2017, with an

expected average increase in oil prices of approximately 15 per cent. In the following years, this

growth rate should slowdown. Compared to the October Economic Bulletin, there is an upward

revision of the level estimated for 2016. For 2017 and 2018, the assumptions for oil prices in

dollars are slightly higher than those included in the June Economic Bulletin. The scale of these

revisions is sharper when prices are measured in euros, given the downward revision of the tech-

nical assumption for the respective exchange rate.

The developments assumed for the three-month EURIBOR are based on expectations implicit in

futures contracts. According to this information, the short-term interest rate is expected to remain

slightly negative in the 2016-18 period, partly reflecting the broad range of monetary policy measu-

res adopted by the ECB. A rise is assumed at the end of the projection horizon, with a zero interest

rate expected in 2019. In turn, the long-term interest rate for Portuguese debt, whose calculation

methodology is based on an estimate of the implicit rate considering an assumption for the interest

rate for new issuances, should be about 3.4 per cent in the 2016-18 period, falling slightly in 2019.

Short interest rates and long-term interest rates for sovereign debt remain essentially unchanged

compared to the assumptions in previous projections.

The technical assumption for exchange rates is based on the maintenance over the projection

horizon of the average levels observed in the two weeks prior to the cut-off date. Therefore, follo-

wing a significant depreciation of the euro in 2015, it is assumed that there will be an appreciation

of the effective exchange rate in annual average terms in 2016 and 2017 that is slightly more

expressive than that included in the October Economic Bulletin.

The projections relating to the public finance variables incorporate the policy measures already

approved (or very likely to be approved) and that are specified with sufficient detail, in line with

the procedure adopted within the scope of the Eurosystem’s projection exercises.

14 BANCO DE PORTUGAL • Economic Bulletin • December 2016

With regard to the State Budget for 2017, the main measures considered include the remai-

ning effect of the phased elimination of the surtax on income tax (IRS) during 2017, the changes

announced in terms of increasing indirect taxation and increasing pensions.

The current projection for 2016 points to a 1.0 per cent change in public consumption in real

terms, largely resulting from growth in intermediate consumption expenditure, which is influenced

by the increase in costs associated with public-private partnerships in the road transport sector.

Furthermore, a very slight increase in public employment has been considered, as well as a preli-

minary estimate, surrounded by uncertainty, of the impact of the reduction in the normal working

hours of public sector employees in the second half of 2016.

From 2017 onwards, moderate growth in public consumption is projected, reflecting the assump-

tion of a reduction in the costs with public-private partnerships (in line with the State Budget Report

for 2017) and the near stabilisation of the annual average number of public sector employees.

In terms of the public consumption deflator, positive rates of change are expected along the pro-

jection horizon. In 2016 and 2017, these developments reflect, in particular, the gradual reversal

of public employees’ pay cuts and, in 2018 and 2019, has an underlying assumption of a wage

update in line with inflation.

In 2016, public investment should fall significantly, only partly explained by the delivery of military

equipment sold and the reversal of the effect associated with the acquisition of real estate by

Oitante in 2015. For 2017, there is expected to be a recovery in public investment, as included in

the State Budget Report for 2017, and in subsequent years developments in this aggregate are

expected to be approximately in line with nominal GDP.

Table 1 • Projection assumptions

EB December 2016

EB October 2016

EB June 2016

2015 2016 2017 2018 2019 2016 2016 2017 2018

International environmentWorld GDP yoy 3.1 2.9 3.3 3.4 3.5 2.9 2.9 3.4 3.5World trade yoy 1.9 1.5 3.2 3.9 4.0 1.8 2.5 4.0 4.3External demand yoy 3.8 2.0 3.4 4.0 4.1 2.8 3.7 4.5 4.7Oil prices in dollars aav 52.4 43.1 49.3 52.6 54.6 42.8 43.4 49.1 51.3Oil prices in euros aav 47.2 38.8 45.3 48.3 50.1 38.4 38.3 42.9 44.9

Monetary and financial conditions

Short-term interest rate (3-month EURIBOR) % 0.0 -0.3 -0.3 -0.2 0.0 -0.3 -0.3 -0.3 -0.3Implicit interest rate in public debt % 3.6 3.4 3.4 3.4 3.3 3.5 3.5 3.5 3.4Effective exchange rate index yoy -9.3 2.8 0.4 0.0 0.0 2.5 2.9 0.3 0.0Euro-dollar exchange rate aav 1.11 1.11 1.09 1.09 1.09 1.11 1.13 1.14 1.14

Sources: ECB, Bloomberg, Thomson Reuters and Banco de Portugal calculations.

Notes: yoy – year-on-year rate of change, % – per cent, aav – annual average value. An increase in the exchange rate corresponds to an appreciation. The implicit interest rate on public debt is computed as the ratio between interest expenditure for the year and the simple average of the stock of debt at the end of the same year and at the end of the preceding year.


3. Supply, demand and external accounts

Recovery in activity and employment, amid low productivity growth

Following 1.6 per cent growth in 2015, GDP is expected to grow by 1.2 per cent in 2016, accel-erating to 1.4 per cent in 2017. Its growth rate should be relatively stable in 2018-19 (1.5 per cent). These developments would imply that GDP levels at the end of the projection horizon will stand close to those seen in 2008, when the international financial crisis began.

In sectoral terms, a lower annual rate of change is projected across most of the main sectors of activity for 2016, particularly in construction and manufacturing, whose value added declined in the first half of the year (Chart 3.1). Over the projection horizon, activity is expected to recover in these sectors. Activity in the services sector – with a share of approximately 74 per cent in gross value added (GVA) – is projected to accelerate moderately in the 2017-19 peri-od, following a slight deceleration in 2016. This sector should continue to benefit from buoy-ant exports, particularly of tourism, but also

as regards services associated with exports of goods, in line with a greater allocation of pro-ductive resources to the sectors most exposed to international competition.

Labour market developments are expected to remain favourable over the projection horizon. Therefore, following strong growth in 2016 – higher than GDP and close to that seen in 2015 (1.5 per cent) – the pace of growth in employment should stand at around 1 per cent in 2017-19, more in line with the historical relationship between employment and activity (Chart 3.2). Employment is projected to grow in the private sector, given that public employment should remain relatively stable. These developments in employment, together with the assumption of a virtual stabilisation in the labour force, imply that the unemployment rate will follow a downward trend over the projection horizon, from 11 per cent in 2016 to 8.5 per cent in 2019 (Chart 3.3).

Developments in economic activity and employ-ment translate into very weak labour productiv-ity dynamics in the recent recovery period. Fol-lowing a slight reduction in 2016, annual labour productivity growth is projected to be approxi-mately 0.5 per cent over the projection horizon.

Chart 3.1 • Overall and sectoral GVA | Index 2008=100

Chart 3.2 • GDP and employment | Annual rate of change

50

60

70

80

90

100

110

120

2008 2009 2010 2011 2012 2013 2014 2015 2016 (p)

2017 (p)

2018 (p)

2019 (p)

GVA Agriculture, forestry and fishingIndustry ConstructionServices

2009

20102011

2012

2013

2014 20152016

20172018

2019

-6

-4

-2

0

2

4

-5 -3 -1 1 3 5

Empl

oym

ent

GDP

Sources: Statistics Portugal and Banco de Portugal.

Notes: (p) – projected. The projections for sectors are based on simple mo-dels that take into account developments in the expenditure components that are more important for each branch of activity.


Note: Values for 2016-19 are projections.


These developments in productivity against a background of economic recovery fall well short of those seen in previous cycles, which is com-mon to other advanced economies, including the euro area (Chart 3.4). However, the reces-sion period prior to the current recovery also posted atypical productivity developments, reflecting employment losses that exceeded those in activity.

The marked fall in investment during the reces-sions of the 2008-12 period, and particularly its impact on the adoption of new technologies and new productive processes, may have lim-ited efficiency gains across most sectors. The allocation of capital in the economy exhibits distortions which limit activity growth, although there is no evidence available for the most recent period.3 Furthermore, the allocation of the labour factor is also inefficient, to the extent that the greater weight of employment remains concentrated in sectors that are less productive than average. However, available data point to a

continued reallocation of employment to more productive sectors of activity or with greater productivity growth, in line with that seen since the onset of the adjustment period.4

The profile projected for GDP per capita is simi-lar to that in activity, under the assumption that the population will remain stable. Breaking down economic growth, developments in GDP

per capita are still largely explained by contribu-tions from labour (0.7 p.p. on average over the projection horizon), given the projected pro-file for employment (Chart 3.5). The contribu-tion of the capital factor should continue to be virtually nil over the projection horizon, given that, despite an upturn in investment, the latter should remain at levels that only make it pos-sible to offset the capital depreciation. This lim-its potential GDP growth, to the extent that new technologies are incorporated into the produc-tive process via the capital factor. Human capi-tal, measured using as proxy the average num-ber of years of completed schooling, should

Chart 3.3 • Employment and unemployment rate | In percentage

Chart 3.4 • Labour productivity: comparison between countries of developments vis-à-vis their previous economic recoveries | Cumulated deviations vis-à-vis the average of previous cycles, by country

8.310.3 11.8 12.7

15.5 16.213.9

12.411.0 10.1

9.4 8.5

-10.0

-5.0

0.0

5.0

10.0

15.0

20.0

-5.0-4.0-3.0-2.0-1.00.01.02.03.04.05.0

2008 2009 2010 2011 2012 2013 2014 2015 2016 (p)

2017 (p)

2018 (p)

2019 (p)

Employment (yoy rate of change) Unemployment rate (rhs)

-15.0

-10.0

-5.0

0.0

5.0

10.0

2008 2010 2012 2014 2016(p)

2018(p)

Euro area Germany SpainFrance Italy Portugal



Sources: European Commission (AMECO), Statistics Portugal and Banco de Portugal.

Notes: (p) – projected. The economic recoveries considered were determined on the basis of the Portuguese business cycle and started in 1984, 1993, 2003 and 2013. The 2009 recovery was not considered due to its limited duration. For each country the values presented correspond to the cumulated change considering 2013 as the reference year minus the cumulated average change of the years 1984, 1993 and 2003.


also make a substantial contribution to aver-age GDP per capita growth over the projection period (0.5 p.p.). Finally, growth in GDP per capita should benefit from a favourable contribution from total factor productivity (around 0.2 p.p., on average, over the projection horizon), partly due to improvements in the allocation of resources in the economy.

Maintenance of stable growth in domestic demand, with a recomposition favourable to investment

Taking into account expenditure components net of their import content, the slowdown in 2016 points to a smaller contribution from domestic demand, more specifically investment (Chart 3.6). Investment components with low import content (e.g. construction) are projected to decrease. In the case of exports, the deceleration in 2016 is associated with components with high import content. As such, although the gross contribution

of exports to GDP is expected to decrease, the same does not hold true when their import con-tent is subtracted. For the 2017-19 period, the contribution from exports net of import content is projected to broadly stabilise. This component will continue to make the highest contribution to GDP growth. Nevertheless, the moderate accel-eration in activity in 2017 and 2018 is expect-ed to be determined by a greater contribution from domestic demand, associated to a recom-position, which points to an upturn in investment and lower consumption growth compared with projections for 2016. In 2019 this composition is expected to be virtually unchanged.

Over the projection horizon, private consump-tion is expected to grow slightly less than activi-ty. Projected developments indicate that the level of consumption will remain marginally above that seen in 2008 at the end of the projection horizon (Chart 3.7).

The relatively buoyant developments in private consumption in the most recent years and those

-2.5

-1.5

-0.5

0.5

1.5

2.5

1999-2010 2011-2015 2016-2019 (p)

Capital stock per capita Employment per capita Total factor productivityHuman capital GDP per capita (a.r.c., in %)

Chart 3.5 • Breakdown of the growth in real GDP per capita | Contributions in percentage points

Sources: Barro and Lee (2013), Quadros de Pessoal, Statistics Portugal and Banco de Portugal.

Notes: (p) – projected. The growth accounting exercise of GDP per capita is based on a Cobb-Douglas production function. The measures of human capital were constructed from the data of Barro and Lee (2013) ’A new data set of educational attainment in the world, 1950-2010′, Journal of Development Economics 104, pp. 184-198. For Portugal, these series were annualized and extended using the profile of the average years of education of employment of Quadros de Pessoal (until 2012) and of the Labour Force Survey of Statistics Portugal (in 2013 and 2014).


projected for 2016 reflect a substantial con-tribution from consumption of durable goods (Chart 3.8). This profile is typical during recov-ery phases of the cycle and is associated with the postponement of the purchase of durable goods during crisis periods, which gives rise to pent-up demand. This demand results in very substantial increases once the recovery starts, but which only imply a return to the target opti-mal stock of durable goods. During the latest recovery phase, this effect was more marked than in the past, possibly because the severi-ty and duration of the recession that preceded it were also higher, and was also influenced by more favourable financing conditions (Chart 3.9). Over the projection horizon, this effect is expect-ed to unwind, which should result in the stabili-sation of the share of consumption of dura-ble goods in GDP. Consumption of non-dura-ble goods should continue to grow by approxi-mately 1.5 per cent in 2017-19, above projected developments for real disposable income. Real disposable income growth should remain rela-tively stable over the projection horizon, reflect-ing a background of muted growth in compen-sation of employees – although higher than that

seen since 2008 – and the impact of fiscal mea-sures with a positive effect on nominal dispos-able income included in the State Budgets for 2016 and 2017, as well as the effect of an accel-eration in the private consumption deflator. These developments in consumer prices part-ly reflect the unwinding of the downward pres-sure on prices stemming from the reduction in oil prices over the most recent years (Section 4. Prices and wages).

Projected developments in private consumption and disposable income should lead to a reduc-tion in the savings rate in 2016, thus extending the downward trend seen in the previous two years. For the 2017-19 period, the projection indicates that the household savings rate should stand, on average, at 3.6 per cent.

Following 4.5 per cent growth in 2015, GFCF should decrease by 1.7 per cent in 2016, return-ing in 2017-19 to rates of change close to those seen in 2015. The reduction estimated for 2016 results from the behaviour of the public GFCF and residential GFCF. Public investment should decrease markedly in 2016, posting relative-ly muted average growth during the following

Chart 3.6 • Gross and net contributions to GDP | In percentage points

Chart 3.7 • GDP breakdown | Index 2008=100

-5.0

-3.0

-1.0

1.0

3.0

5.0

2015 2016 (p) 2017 (p) 2018 (p) 2019 (p)

Private consumption Public consumption InvestmentExports Imports GDP (a.r.c in %)

60

80

100

120

140

160

2008 2009 2010 2011 2012 2013 2014 2015 2016(p)

2017(p)

2018(p)

2019(p)

GDP Private consumptionGFCF Exports


Notes: (p) – projected. For each year, the left-hand bar refers to gross contribu-tions from each GDP component and the right-hand bar to the corresponding net contributions.




years (Box ‘Projection assumptions‛). Develop-ments in this component during 2016 are sub-ject to particular uncertainty due to the late entry into force of the budget for this year and taking into account the expenditure profile associat-ed with investment projects co-funded by Euro-pean Union funds. The transfer of EU funds to final beneficiaries in the first half of the year was lower than usual, amid a transition to the NSRF 2014-2020. This is expected to also have affected GFCF in the private sector over the same period. GFCF in housing is expected to decline by 3.4 per cent in 2016, only to grow moderately, by around 2 per cent, over the remaining projection horizon. Developments in this sector have been negative almost without interruption since 2000, reflecting the sector’s restructuring in response to struc-tural constraints. In 2017-19 projections point to a return to positive rates of change, although subdued, as a result of gradual improvements in labour market conditions and the maintenance of favourable financing conditions. Develop-ments in this variable should continue to be lim-ited by the evolution of the resident population, which has presented a downward trend, and by the high indebtedness of households.

Projections indicate that corporate GFCF will accelerate, from 1.9 per cent in 2016 to 5.6 per cent in 2019, in line with improved domestic and external demand expectations, against a back-ground of sustained favourable financing con-ditions, which should continue to benefit from the impact of the ECB’s non-standard mone-tary policy measures (Special issue ‘Life below zero: monetary policy transmission under nega-tive interest rates‛). Over the projection horizon, the share of this component in GDP is expected to increase, which would lead to a return to the average value posted in 1999-2005. However, in 2019, the corporate GFCF level is projected to remain below that seen in 2008, although the deviation should be lower than for the remain-ing GFCF components by institutional sector (Chart 3.10).

From 2016 onwards, the total GFCF recovery pro-file is projected to be relatively weak compared with previous recovery periods, being mostly in line with the upturn that followed the 2003 cri-sis (Chart 3.11), despite the fact that the current crisis has been much more marked than previ-ous ones. These comparatively weaker develop-ments in GFCF have also been recorded in other

Chart 3.8 • Private consumption and disposable income | Rate of change in percentage and contributions in percentage points

Chart 3.9 • Weight of durables consumption on GDP | In percentage of GDP

-10.0

-5.0

0.0

5.0

2008 2010 2012 2014 2016 (p) 2018 (p)

Non-durables consumptionDurables consumptionPrivate consumption (a.r.c. in %)Real Disposable inome (a.r.c. in %)

0.0

2.0

4.0

6.0

8.0

10.0

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

2017

(p)

2019

(p)


Notes: (p) – projected.


Notes: (p) – projected. The shaded areas denote the beginning of the recovery periods of the Portuguese business cycle, which occurred in 1984, 1993, 2003 and 2013. The 2009 recovery was not considered due to its limited duration.


euro area countries, particularly Spain and Ita-ly (Chart 3.12). A number of factors is contribut-ing to this relative weakness which, although also relevant at the European level, may be amplified in the case of Portugal. Against this background, it is worth noting that the outlook for private GFCF over the projection horizon is limited by private sector deleveraging needs, given that, despite

some reduction since the onset of the finan-cial crisis, indebtedness of households and non-financial corporations remains high compared with other EU countries (Chart 3.13). This down-ward trend in indebtedness is expected to con-tinue over the projection horizon, in the case of both households and non-financial corporations, but more marked for households (Chart 3.14).

Chart 3.10 • Breakdown of

GFCF by institutional

sectors | Index 2008=100

40

60

80

100

120

140

160

2008 2009 2010 2011 2012 2013 2014 2015 2016 (p) 2017 (p) 2018 (p) 2019 (p)

Total GFCF Business Residential Public



Chart 3.11 • Developments in GFCF in different economic recoveries | Index T=100

Chart 3.12 • Comparison between countries of developments in GFCF vis-à-vis previous economic recoveries | Cumulated deviations vis-à-vis the average of previous cycles, by country

80

130

180

230

T T+2 T+4 T+6 T+8 T+10

1984 1993 2003 2013

-20.0

-15.0

-10.0

-5.0

0.0

5.0

2014 2015 2016 (p) 2017 (p) 2018 (p)

Euro area Germany SpainFrance Italy Portugal


Notes: The economic recoveries considered were determined on the basis of the Portuguese business cycle and started (T) in 1984, 1993, 2003 and 2013. The 2009 recovery was not considered due to its limited duration. The dotted line corresponds to the projection period.


Notes: (p) – projected. The economic recoveries considered were determined on the basis of the Portuguese business cycle and started in 1984, 1993, 2003 and 2013. The 2009 recovery was not considered due to its limited duration. For each country the values presented correspond to the cumulated change consi-dering 2013 as the reference year minus the cumulated average change of the years 1984, 1993 and 2003.


Developments in private GFCF may be limited by the downward revision to medium-term eco-nomic growth expectations, a factor also asso-ciated with the slow pace of recovery in private investment in several euro area countries. The projected profile of public investment also differs from previous recovery periods, reflecting the current need for fiscal consolidation.

Very strong growth in exports, leading to continued market share gains

Following very buoyant growth in 2015 (6.1 per cent), exports of goods and services are expect-ed to decelerate in 2016 (3.7 per cent), recover-ing to a pace of growth of 4.8 per cent in 2017 and 4.6 and 4.4 per cent in 2018 and 2019 respectively. The slowdown in 2016, which is not expected to hinder new market share gains, reflects a deceleration in external demand (Box ‘Projection assumptions‛) and a number of tem-porary factors, such as reduced production in industrial plants of the automotive and ener-gy sectors. Furthermore, in 2016 exports con-tinued to reflect the unfavourable performance

of sales to a number of non-EU markets, par-ticularly Angola (despite a lower decrease in the second half of the year). In 2017 the unwinding of these factors, together with a projected accel-eration in external demand, should contribute to a return of exports to more buoyant growth. Exports of goods should also benefit in 2017 and 2018 from the improved productive capac-ity of an automotive plant, which should contrib-ute to keeping growth in this component above external demand.

Exports of services are also projected to grow more than external demand over the projection horizon. Although tourism exports are projected to decelerate, they should remain highly buoyant.

As a result of these developments, the Portu-guese economy is expected to continue to post market share gains over the projection horizon, although gradually more subdued, leading to the slight deceleration in exports projected for 2018 and 2019 (Chart 3.15). These market share gains are more marked in 2016 (as in 2015) if exter-nal demand assumptions are refined by taking into account the specific developments in the Angolan economy over this period. The buoy-ancy of exports over the projection horizon is

Chart 3.13 • Debt of the non-financial private sector, in the European Union, in 2015 | End of period figures in percentage of GDP

Chart 3.14 • Debt of the non-financial private sector in Portugal | End of period figures in percentage of GDP and disposable income

0

50

100

150

200

250

300

350

400

Cypr

usLu

xem

bour

gIre

land

Net

herla

nds

Den

mar

kSw

eden

Port

ugal

Belg

ium

Uni

ted

King

dom

Finl

and

Spai

nFr

ance

Mal

taG

reec

eAu

stria Italy

Esto

nia

Croa

tiaBu

lgar

iaG

erm

any

Latv

iaSl

oven

iaH

unga

rySl

ovak

iaPo

land

Czec

h Re

publ

icRo

man

iaLi

thua

nia

70

80

90

100

110

120

130

140

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017(p)

2019(p)

Non-financial corporations – Total debt (a) (as a % of GDP)Households debt (b) (as a % of disposable income)

Source: Eurostat. Sources: Statistics Portugal and Banco de Portugal.

Notes: (p) – projected. Consolidated values. (a) It includes loans granted to non-financial corporations by other institutional sectors; commercial paper and bonds issued by non-financial corporations held by other sectors and trade credits received from other sectors. (b) The debt of households corresponds to loans and debt securities issued by the sector and trade credit and advances.


expected to result in the continued increase in their share of GDP, even when excluding their import content. Therefore, in 2019 the share of exports in GDP should stand at 48 per cent, compared with 32 per cent in 2008 (net of import content, this share should increase from approximately 20 per cent to around 27 per cent in the same period).

The current projection points to a deceleration in imports of goods and services in 2016, to 3.5 per cent, following very substantial growth in 2015 (8.2 per cent). In the 2017-18 period, imports are expected to accelerate further to near 5 per cent, only to decelerate to 4.5 per cent in 2019. This profile reflects developments in imports closely in line with their historical elasticity to import-content weighted over-all demand, implying a continued increase in import penetration over the projection horizon, although more moderately than in more recent years (Chart 3.16).

The analysis of the allocation of imports to expen-diture components according to their import content, i.e. the counterpart of Chart 3.6, shows that over the recovery period that started in 2013 expenditure components which made the largest

contribution to import growth were exports, with its annual variability being largely due to the energy component, and private consumption (Chart 3.17). The importance of the latter reflects the effect of the purchase of durable goods, due to its high import content. Over the projection horizon, as this effects unwinds, exports should remain the main component behind import growth.

The very buoyant developments projected for exports and imports are expected to imply that the upward trend, more marked since 2010, in the openness of the Portuguese economy (mea-sured by the average share of both trade flows in GDP, in nominal terms) will continue, following a slight decrease in 2016 (Chart 3.18). However, there is no such temporary reduction when the indicator is calculated in real terms.

Lower external net lending compared with previous years

The current projection points to the mainte-nance of a net lending position of the Portu-guese economy, measured by the combined current plus capital accounts balance, although below the levels seen in recent years. Therefore,

Chart 3.15 • Exports of goods and services and external demand | Annual rate of change, in percentage

Chart 3.16 • Imports and import-content weighted final demand | Annual rate of change, in percentage

-20.0

-10.0

0.0

10.0

20.0

2000 2002 2004 2006 2008 2010 2012 2014 2016(p)

2018(p)

Cumulative change in market share (p.p.)ExportsExternal demandExternal demand adjusted for Angola effect

-10.0

-5.0

0.0

5.0

10.0

2008 2009 2010 2011 2012 2013 2014 2015 2016 (p)

2017 (p)

2018 (p)

2019 (p)

Import penetration (p.p.) Weighted final demandImports

Sources: Statistics Portugal, IMF, ECB and Banco de Portugal.

Notes: (p) – projected. The change in market share was computed with the external demand not adjusted for the Angola effect.




after reaching 1.7 per cent of GDP in 2015, the combined current plus capital accounts balance is projected to decline to 1.1 per cent of GDP in 2016, standing close to this level up to the end of the projection horizon. The reduction in the balance as a percentage of GDP in 2016 will be broadly based across the main accounts, excluding the trade balance. Namely, the second-ary income account has been affected by lower emigrant remittances – in particular, from Swit-zerland (the second most important issuer of remittances to Portugal, with a share of approxi-mately 26 per cent in 2015) – and other private transfers. This impact is assumed to persist over the projection horizon. In the case of the capital account, EU funds have been transferred to final beneficiaries to a lesser extent than in the previ-ous year, which may be associated with the cur-rent transition to a new NSRF. The current pro-jection points to some recovery in these flows during the second half of 2016 and a stabilisa-tion in the capital account balance as a percent-age of GDP over the remaining projection hori-zon, to a level close to that seen in 2015. The pri-mary income account deficit as a percentage of GDP is expected to increase in 2016, only to fol-low a slight downward path until the end of the

projection horizon, benefiting from the techni-cal assumption for the implicit interest rate on public debt. The trade balance surplus as a per-centage of GDP is expected to increase some-what in 2016 and decline in 2017 to a level close to that seen in 2015, and to stabilise over the remaining projection horizon. This variability in the balance reflects developments in terms of trade, partly offset by volume and price effects (Chart 3.19). Changes in terms of trade seen since 2012, which only partly result from oil price developments, made a very substantial contribution to the external adjustment in the Portuguese economy. Between 2012 and 2015, cumulative change amounting to 2.5 p.p. of GDP in the trade balance can be imputed to terms of trade gains, while in the case of the trade bal-ance excluding energy goods the terms-of-trade effect stood at 1.4 p.p. of GDP.

The reduction in net lending in 2016 reflects a decrease in aggregate savings in the economy and, to a lesser extent, capital transfers as a per-centage of GDP, only partly offset by a low invest-ment rate. For 2017-19, rates are expected to follow an upward path in terms of both savings and investment compared with projections for

Chart 3.17 • Allocation of imports to expenditure components | Contributions to the annual rate of change in percentage points

Chart 3.18 • Exports, imports and degree of openess | In percentage of GDP

-10.0-8.0-6.0-4.0-2.00.02.04.06.08.010.0

2011 2012 2013 2014 2015 2016(p)

2017(p)

2018(p)

2019(p)

Private consumption Public consumptionGFCF Change in inventoriesExports Imports (a.r.c, in %)

25.0

30.0

35.0

40.0

45.0

50.0

1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 (p)

2019 (p)

Imports Exports Degree of openness



Source: Statistics Portugal and Banco de Portugal.

Note: (p) – projected. The degree of openess is measured by the ratio of the average of exports and imports to GDP, in nominal terms.


2016, although still below those seen in 2015. The private sector’s net lending as a percentage of GDP should remain relatively stable in the 2017-19 period, although below in the levels for 2016, for both households and enterprises.

Downward revision of GDP growth from June projections and slightly upward revision from October projections

Current projections point to GDP growth in 2016 slightly above that underlying projections pub-lished in the October issue of the Economic Bulle-tin. This upward revision resulted from the incor-poration of information for the third quarter, par-ticularly exports net of import content, which reflected higher than expected growth during that quarter.

Compared with the June 2016 issue of the Eco-nomic Bulletin, projections for GDP growth in 2016 and 2017 were revised down (0.1 p.p. in 2016 and 0.2 p.p. in 2017), due to more muted pros-pects for domestic demand. For 2016, the revi-sion of domestic demand was chiefly due to GFCF, reflecting the incorporation of quarterly nation-al accounts data for the second quarter of 2016

and annual accounts for 2015. For 2017, the revi-sion of domestic demand largely reflects expec-tations of more muted developments in private consumption. By contrast, exports were revised upwards for 2016 and 2017, despite the down-ward revision of the external demand for Portu-guese goods and services, reflecting the incorpo-ration of the latest available data. For 2018, pro-jections for GDP growth and its composition are relatively unchanged from the June issue of the Economic Bulletin. Projections for the current plus capital account balance as a percentage of GDP were revised downwards from the June issue of the Economic Bulletin and, in the case of 2016, also from the October issue of the Economic Bul-letin. These revisions reflect the incorporation of the latest balance of payments data.

4. Prices and wagesInflation, as measured by the rate of change in the HICP, is expected to stand at 0.8 per cent in 2016, compared with 0.5 per cent in 2015. Along the projection horizon, inflation should increase progressively (1.4 per cent in 2017 and 1.5 per cent in 2018 and 2019) as a result of growing positive contributions of the non-energy compo-nent, in parallel with a less negative contribution

Chart 3.19 • Decomposition

of the change in the balance of goods and

services account | In percentage

points of GDP

-4.0

-2.0

0.0

2.0

4.0

6.0

2008 2009 2010 2011 2012 2013 2014 2015 2016 (p) 2017 (p) 2018 (p) 2019 (p)

Volume effect Price effect

Terms of trade effect Change in the balance of goods and services account (as a % of GDP)


Notes: (p) – projected. For more details on the methodology used, see Box 4.2 ’Change in the goods account balance in the first half of 2012‛, Economic Bulletin Banco de Portugal, Autumn 2012.


of the energy component in 2016, becoming pos-itive in the following years (Chart 4.1). Compared to the figures published in the June and October issues of the Economic Bulletin, inflation levels for the period 2016-19 remained mainly unchanged.

In comparison with the projections for the euro area released by the ECB on 8 December, infla-tion is expected to remain 0.6 p.p. above the euro area average in 2016, chiefly reflecting a lower fall in energy prices in Portugal, amid rises in tax-es associated with these goods. For the follow-ing years, the differential vis-à-vis the euro area is expected to narrow, becoming slightly negative at the end of the projection horizon (Chart 4.2).

The inflation rate should increase somewhat in 2016, to 0.8 per cent, reflecting a lower fall in energy and non-energy industrial goods prices and a slight acceleration in services prices. In par-ticular, these developments in services are quite evident in segments related to more dynamic sectors such as tourism. On the other hand, food prices are expected to decelerate, with special notice to the projected slowdown in processed food prices.

With regard to the impact on consumer prices of taxation measures applied in 2016, the estimated

effect is relatively small, since the positive effect resulting from the rise in taxes on various prod-ucts (notably oil products, vehicles and tobac-co) was partly offset by a reduction of VAT in restaurants, which entered into force in July this year.

In 2017 consumer prices are expected to accel-erate significantly, to 1.4 per cent, largely as a result of the expected recovery in energy prices (approximately 3 per cent growth, after -2.1 per cent in 2016), in line with the path assumed for oil prices. This positive base effect is expected to dissipate in the following years, with projections pointing to progressively lower increases in ener-gy prices. In this vein, the slight rise in inflation in 2018 is chiefly accounted for by an acceleration in the non-energy component. For 2019 inflation is projected to stabilise at 1.5 per cent.

The upward path expected for inflation excluding energy in the 2017-19 period reflects an under-lying increase in domestic and external inflation-ary pressures, fostered by economic growth at national and global levels, the positive impact of monetary policy measures adopted by the ECB, and the incorporation of technical assumptions of a rise in commodity prices in euros. Although broadly based, the upward profile is particularly

Chart 4.1 • Harmonised index of consumer prices | Contributions to the annual rate of change, in percentage points

Chart 4.2 • Harmonised index of consumer prices in Portugal and in the euro area | Annual rate of change, in percentage

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

2008 2009 2010 2011 2012 2013 2014 2015 2016 (p)

2017 (p)

2018 (p)

2019 (p)

Excluding energy goods Energy goods HICP (%)

0.5

0.8

1.41.5 1.5

0.00.2

1.31.5

1.7

0.0

0.5

1.0

1.5

2.0

2015 2016 (p) 2017 (p) 2018 (p) 2019 (p)

Portugal Euro area

Sources: Eurostat and Banco de Portugal.


Sources: ECB, Eurostat and Banco de Portugal.



noticeable in non-energy industrial goods prices, which recorded negative rates of change since 2012. In this scenario, the growth rate of non-energy goods import prices is projected to be approximately 2 per cent in 2017-19, compared with a reduction in 2016.

Moderate wage growth and slight acceleration in the private sector GDP deflator

Developments projected for inflation show an underlying profile of gradual acceleration in wag-es per employee, in a scenario of increase in pro-ductivity and gradual improvement in the labour market situation. Unit labour costs are expect-ed to continue to grow at a relatively stable rate in the 2017-19 period, both in the economy as a whole and the private sector. In this context, a slightly upward growth path is projected for the private sector’s GDP deflator,5 reflecting the absence of further inflationary pressures (on average, the contributions from unit labour costs and the gross operating surplus per unit of out-put are relatively similar) (Chart 4.3). The trend of the private sector GDP deflator in 2015 and 2016 reflected on the one hand a marked increase in the gross operating surplus per unit in 2015

– influenced by improved terms of trade – and

on the other the impact of a 5 per cent rise in

the minimum wage in 2016.

Increase in inflation expectations

Inflation expectations for the next 12 months

(calculated on the basis of data released by Con-

sensus Economics) follow an upward path both in

Portugal and the euro area. However, the expect-

ed levels are substantially lower than the ECB’s

price stability objective, which envisages a rate of

change in the HICP close to but below 2 per cent

in the medium term (Chart 4.4).

5. Uncertainty and risks

Downward risks for economic activity in 2017-18 and for inflation in 2018

This section presents a quantified review of risks

and uncertainties surrounding the current pro-

jection, which corresponds to the most likely

scenario, given the set of assumptions consid-

ered. However, the non-materialisation of these

Chart 4.3 • Decomposition of the private sector GDP deflator | Contributions to the annual rate of change, in percentage points

Chart 4.4 • Inflation expectations for a 12-month horizon | Annual average rate of change, in percentage

-2.0-1.5-1.0-0.50.00.51.01.52.02.53.0

2008 2009 2010 2011 2012 2013 2014 2015 2016(p)

2017(p)

2018(p)

2019(p)

Unit labour costsGross operating surplus per unit of outputIndirect taxes less subsidiesPrivate sector GDP deflator (%)

-0.5

0.0

0.5

1.0

1.5

2.0

Jan.13

May

13

Sep.13

Jan.14

May

14

Sep.14

Jan.15

May

15

Sep.15

Jan.16

May

16

Sep.16

Portugal Euro area



Sources: Consensus Economics and Banco de Portugal calculations.


assumptions, as well as the possibility of occur-rence of factors that, for their characteristics, were not taken into account in the current pro-jection, give rise to risks and may alter the rel-evant levels of uncertainty surrounding the cen-tral scenario.

Although the business cycle recovery phases are always associated with a greater degree of uncertainty, the unprecedented nature of large adverse shocks that have affected the Portu-guese economy in the past few years causes perspectives to become more uncertain in the projection horizon. Hence, by conditioning eco-nomic agents’ expectations with regard to fu-ture economic prospects, uncertainty may be an important factor limiting economic growth (Box: ‘Impact of uncertainty measures on the Portuguese economy‛).

Against this background, the uncertainty around the United States’ economic policy guidelines, as well as the evolution of the United King-dom’s relations with the European Union and a possibly weaker recovery of emerging market economies give rise to risks of a potentially less dynamic evolution of activity and trade flows at the global level over the course of the projection horizon. These risk factors may translate into lower growth of the external demand for Portu-guese goods and services and a further appre-ciation of the euro in 2017-18, also leading to higher uncertainty levels.

The possibility of renewed tensions in financial markets cannot be excluded, and there is also some uncertainty as to the configuration of the ECB’s non-standard monetary policy over the projection horizon. In addition, the vulnerabil-ity of the banking system or the fiscal position in a number of euro area countries may lead to a rise in sovereign debt interest rates. These aspects assume a special relevance at domes-tic level, in a context of persistent risks for finan-cial stability in Portugal.6 These factors may lead to an increase in the economy’s financing costs, with an impact on private consumption and investment. In addition, one should consider

the possible need for additional fiscal consoli-dation measures to comply with the objectives assumed in the medium term, with a negative impact on domestic demand developments.

Downward inflation risks are considered for 2017-19, given that the pressure on prices stem-ming from a weaker evolution of activity is rein-forced by the risk of inflation expectations in the euro area remaining below the ECB’s monetary policy objective, which may have a negative impact on prices. In addition, a downward risk for pric-es in 2017-18 resulting from the maintenance of production overcapacity at global level is also considered, which may create competitive pres-sures with an impact on inflation. Finally, the pos-sibility of a further rise in the minimum wage in 2017 has also been taken into account.

As a result of this assessment of risks and uncer-tainty, a 55 per cent probability was considered of a more unfavourable evolution of external demand and a sharper appreciation of the euro than considered in the central scenario in 2017-18 (Table 5.1). Developments in domestic demand components were also assessed as potentially weaker than in the projection, with a 53 per cent probability in private and public consumption and 55 per cent in investment. In addition, the possibility of more marked wage growth in 2017 was considered (with a 60 per cent probability), as well as of a more moderate evolution of inflation in 2017-18 (with a 55 per cent probability).

This analysis implies downward risks for activity in 2017-18. Inflation risks are considered balanced in 2016-17 and downward in 2018 (Table 5.2 and Charts 5.1 and 5.2).7


Table 5.1 • Risk factors – Probability of an outcome below the implicit in the projections | In percentage

2016 2017 2018

Projection assumptionsExternal demand 50 55 55Exchange rate 50 45 45Public consumption 50 53 53

Endogenous variablesPrivate consumption 50 53 53GFCF 50 55 55Wages 50 40 50HICP 50 55 55


Table 5.2 • Probability of an outcome below the projections | In percentage

Weights 2016 2017 2018

Gross domestic product 100 50 55 58Private consumption 66 49 53 55GFCF 15 50 56 58Exports 41 49 54 56Imports 40 50 55 58

HICP 49 49 57


Chart 5.1 • Gross domestic product | Rate of change, in percentage

Chart 5.2 • Harmonized index of consumer prices | Rate of change, in percentage

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Gráfico 5.1 Gráfico 5.2Produto interno bruto Índice harmonizado deTaxa de variação, em percentagem Taxa de variação, em p

Cenário central Int. de confiança a 40 % Int. de confiança a 60 %

Fonte: Banco de Portugal. Fonte: Banco de Portug

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2012 ‐3,3 ‐3,3 ‐3,3 ‐3,3 ‐3,3 ‐3,3 ‐3,3 2,82013 ‐1,4 ‐1,4 ‐1,4 ‐1,4 ‐1,4 ‐1,4 ‐1,4 0,42014 0,3 0,5 0,6 0,9 1,1 1,2 1,4 ‐0,32015 ‐0,2 0,3 0,7 1,5 2,0 2,4 2,9 ‐0,62016 ‐1,1 ‐0,3 0,3 1,6 2,2 2,9 3,6 ‐0,9




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6. ConclusionsThe Portuguese economy has maintained a mod-erate recovery trajectory since 2013, particular-ly when compared to that observed in previ-ous comparable phases of the cycle. The projec-tions in this Bulletin point to an activity growth in Portugal at a level close to that projected for the euro area in the 2017-19 period. In a progressive-ly more favourable external framework, the eco-nomic recovery is likely to continue to be sup-ported by the buoyancy of exports. As regards domestic demand, a recomposition is project-ed, characterised by a deceleration of private consumption – with growth slightly below that of GDP – and dynamic behaviour of GFCF. These features are consistent with the ongoing reori-entation of productive resources towards sec-tors more exposed to international competition and also more productive, with the additional net creation of jobs and a further reduction in unem-ployment, with the maintenance of a surplus in external accounts and the continuation of the process of non-financial private sector’s indebt-edness reduction. Hence, the pattern of the pro-jected economic growth presents a set of fea-tures that reflect a more sustained recovery of the Portuguese economy.

However, various structural constraints to Portu-guese economic growth persist, including the high level of indebtedness of the different economic sectors – households, non-financial corporations and public sector – unfavourable demographic

developments, a high level of long-term unem-

ployment, and a recovery pace of investment fall-

ing short of that observed in previous recoveries.

The impact of these factors tends to be exacer-

bated in the current context of uncertainty, at the

domestic and external levels.

Therefore, it is important that the structural re-

form process is deepened, thus increasing in-

centives to innovation, factor mobility and in-

vestment in human and physical capital, paving

the way for a sustained increase in productivity

and the economy’s growth potential. In addition,

against a background of prevailing relatively high

uncertainty levels, the maintenance of a predict-

able institutional and tax framework will contrib-

ute to preserve investor confidence and ensure

a favourable environment for investment. The in-

itiatives under way to reduce financial and bank-

ing sector’s specific vulnerabilities will also tend

to contribute to this result. The effort to reduce

private economic agents’ level of debt should

be pursued so as to reinforce the resilience to

shocks that affect their debt service capacity. Fi-

nally, additional fiscal consolidation is key to en-

sure that the level of public indebtedness shows

a downward path that is sustained and robust

to adverse shocks. The temporary nature of the

current broad set of non-standard monetary

policy measures in the euro area reinforces the

urgency and importance of structural progress

in these various dimensions.

Box 2 | Impact of uncertainty measures on the Portuguese economy

The purpose of this box is to assess the impact of uncertainty on economic activity developments (GDP) and gross fixed capital formation (GFCF) in Portugal in recent years. Uncertainty has often been considered as a driver of weak developments in advanced economies following the 2008 financial crisis. Although several possible channels point to a negative link between uncertainty and economic activity, this type of association has yet to be empirically analysed in greater detail in the case of the Portuguese economy.8

When deciding on consumption, investment and other expenditure, economic agents must form expectations on relevant future events on the basis of available data. These expectations focus on


uncertainty about the likelihood of alternative events. Therefore, economic uncertainty reflects the unforeseeability of the future economic outlook, to the extent that the likelihood of alternati-ve events is unknown or impossible to gauge with precision. Economic theory suggests that there are several transmission channels of uncertainty to economic activity, more specifically through the postponement of agents’ consumption and investment decisions, in conjunction with their potential effects on the labour and financial markets.9

The purpose of this box is to review developments in a number of uncertainty measures available for Portugal and gauge the impact of these variables on macroeconomic developments in recent years, particularly on GDP and GFCF. Indeed, several empirical applications to assess the effects of uncertainty on economic agents’ decisions focus precisely on economic activity measures and investment.

The uncertainty indicators addressed in this Box are: Banco de Portugal’s composite financial stress indicator for Portugal (Portuguese acronym: ICSF), analysed in Braga et al. (2014), and the economic policy uncertainty indicator for Europe presented in Baker et al. (2015). These indica-tors differ, as they focus on financial and political aspects respectively.10

The purpose of the financial stress indicator for Portugal is to capture systemic stress in the eco-nomy, combining information from several indicators that makes it possible to capture volatility in five market segments, more specifically the money, bond, stock and foreign exchange markets, as well as financial intermediaries. In turn, the economic policy uncertainty indicator is built based on the counting of press articles mentioning ‘uncertainty’, ‘economy’ and an expression relevant to the economic policy in the four largest euro area economies and the United Kingdom. No such indicator has been specifically built for the Portuguese economy, but given its features as a small open economy, its degree of integration – euro area and the EU – as well as its exposure to eco-nomic and political developments at European level, the measure built for Europe shows a high negative correlation with the Portuguese business cycle (Chart 1).

Chart 1 shows developments in uncertainty measures11 since 2002, during which they have pos-ted a negative correlation with the year-on-year rate of change in GDP. A shaded area in the chart signals the last three recessions in Portugal, with the last two being also observed in the euro area. All indicators point to an increase in uncertainty in 2008 (with the collapse of the Lehman

Chart 1 • Evolution of the uncertainty indicators

Economic policy uncertainty indicator for Europe

Composite indicator of financial stress for Portugal

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Sources: website Economic Policy Uncertainty (http://www.policyuncertainty.com) and Banco de Portugal.

Note: The shaded areas denote periods of recession in Portugal.12

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Brothers) and 2011 (euro area sovereign debt crisis), although in the case of the economic policy uncertainty indicator this increase was very muted during the 2008 international financial crisis. These diverging performances during recessions, as well as in the most recent period, are likely to be related to the nature of these indicators. The recession that began in 2008 started as a finan-cial crisis, and therefore its impact on uncertainty is better assessed by looking at the financial stress indicator. Furthermore, the sovereign debt crisis gave rise to questions as regards the euro area institutional framework and, as such, is more relevant in terms of the economic policy uncer-tainty indicator. This indicator also increased further in the most recent period, in the wake of the outcome of the UK’s referendum on EU membership (so-called Brexit).

The importance of uncertainty to macroeconomic developments was estimated on the basis of Bayesian structural VAR (SVAR) models13 for GDP and GFCF in levels.14 This analysis was similar to that described by the European Commission (2015) and Deutsche Bundesbank (2016).

The models were initially estimated in a reduced version that includes a number of regressors that are typically considered in literature.15 This version was re-estimated by adding both uncer-tainty measures alternately. Finally, a third version was estimated covering the previous two plus a measure of private sector leverage.16 Therefore, in its comprehensive version, the model for GDP includes as covariates an uncertainty measure, inflation, employment, the stock of loans to households and non-financial corporations (as proxy for indebtedness levels) and the short--term interest rate. In the case of GFCF, the set of covariates in the model is similar, with the exclusion of employment and the proxy for household indebtedness.

The out-of-sample conditional forecast ability of these models was analysed in the period following the sovereign debt crisis. As such, it is possible to assess whether uncertainty measures would have helped explain recent macroeconomic developments, assuming that all model variables were known. Results show that, overall, both on an individual basis and together with indebtedness mea-sures, uncertainty measures have improved the model forecasts for GDP and GFCF. These results are confirmed by a dynamic analysis using a mean-adjusted SVAR model fitted to the first differen-ces of the series.17

Charts 2 and 3 show the impact of uncertainty on GDP (assessed on the basis of the composite financial stress indicator) and GFCF (on the basis of the economic policy uncertainty indicator).18 The uncertainty indicator included in the model for each macroeconomic aggregate was chosen on the basis of the indicator that originated the lowest conditional forecast errors for the period following the sovereign debt crisis. The chart shows that uncertainty may have a non-negligible impact on GDP and GFCF, with a one standard deviation shock19 on the uncertainty indicator having a maxi-mum impact close to -1 percentage point on the macroeconomic aggregate under review.

These estimated models may be used to break down the rate of change in GDP and GFCF over time. Chart 4 illustrates the outcome of this approach for GDP, up to the third quarter of 2016. The results show that although changes in GDP have been determined by other shocks other than those originated by uncertainty, it had a substantial negative impact during the recessions associated with the financial crisis and the sovereign debt crisis. In turn, uncertainty factors had a positive effect in 2014, which may be associated with the conclusion of the Economic and Financial Assistance Programme. More recently, this positive effect has been unwinding, turning negative as of the first quarter of 2016, when perceived uncertainty increased across Europe, closely associated with a relatively negative review of the European banking sector and, subse-quently, with the consequences of the outcome of the UK’s referendum. In the case of the GFCF, results were similar (Chart 5) when estimating the model up to the second quarter of 2016. In this case, it is worth noting that in the first half of 2016 the fall in GFCF in Portugal was largely due to an increase in uncertainty.


Chart 5 • Historical decomposition of GFCF y-o-y rate of change with the Economic Policy Uncertainty Indicator | Contributions in percentage points

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Chart 4 • Historical decomposition of GDP y-o-y rate of change with the Composite Index of Financial Stress | Contributions in percentage points

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Chart 2 • Impact on GDP of a standard deviation shock measured by the ICSF| In percentage points

Chart 3 • Impact on GFCF of a standard deviation shock measured by the EPU| In percentage points

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ReferencesBaker, S. R., Bloom, N. and Davis, S. J., 2015. ‘Mea-suring Economic Policy Uncertainty.‛ NBER Wor-king Papers 21633, National Bureau of Economic Research, Inc.

Braga, J. P., Pereira, I. and Reis, T. B., 2014, ‘Compo-site indicator of financial stress for Portugal‛, Banco de Portugal Financial Stability Papers, issue 1.

European Commission, 2015, ‘Investment dyna-mics in the euro area since the Crisis‛, Quarterly Report on the Euro Area, Vol 14, number 1.

Deutsche Bundesbank, 2016, ‘Determinants of investment activity in the euro area from the pers-pective of an SVAR model‛, Deutsche Bank Monthly Report, January.

Dieppe, A., Legrand, R., and van Roye, B., 2016, ‘The BEAR toolbox‛, European Central Bank Wor-king paper series, number 1934, July.

Haddow, A., Hare, C., Hooley, J. and Shakir, T., 2013, ‘Macroeconomic Uncertainty: What is it, How Can We Measure It and Why Does it Mat-ter?‛, Bank of England Quarterly Bulletin, 53.

IMF, 2012, ‘How Does Uncertainty Affect Growth‛, Box 1.3, Chapter 1, World Economic Outlook, October.

Jarociński, M. and Smets, F., 2008, ‘House Prices and the stance of Monetary Policy,‛ European Cen-tral Bank Working Paper Series, number 0891, April.

Schneider, J. and Giorno, C., 2014, ‘Economic Uncertainties and their Impact on Activity in Greece compared with Ireland and Portugal‛, OECD Economics Department Working Papers, No. 1151, OECD Publishing, Paris.

Gunnemann, J., 2014, ‘The impact of policy-rela-ted uncertainty on the economy: New evidence from Europe‛, mimeo.


Notes1. Considering non-seasonally adjusted data, the current plus capital account balance as a percentage of GDP was negative (-1 per cent) in the first half of 2016, having fallen compared to the first half of 2015 (-0.1 per cent). Based on seasonally-adjusted data, this balance was positive albeit lower than that recorded in the first half of 2015.

2. In particular, nominal goods exports to Spain showed a year-on-year rate of change of 9.3 per cent in the third quarter of 2016, compared to 3.7 per cent in the first half.

3. Dias, D., Marques, C. R. and Richmond, C., ‘Resource allocation, productivity and growth in Portugal‛, Economic Bulletin, October 2014, Banco de Portugal.

4. See the box entitled ‘Productivity and job reallocation in Portugal‛, Economic Bulletin, October 2016, Banco de Portugal.

5. The private sector GDP refers to total GDP excluding public compensation of employees and fixed capital consumption.

6. See the November 2016 issue of the Financial Stability Report.

7. This Economic Bulletin is the first where the projection horizon exceeds 3 years, and thus it is not possible to quantify the risk assessment for 2019, since the methodology used requires information on historical projection errors for every horizon. The methodology used in this section is based on the article published in Pinheiro, M. and Esteves, P. (2010), ‘On the uncertainty and risks of macroeconomic forecasts: Combining judgements with sample and model information‛, Empirical Economics, pages 1-27.

8. Schneider, J. and Giorno, C. (2014), present a comparative analysis of the impact of uncertainty in Greece, Portugal and Ireland, which focuses solely on stock market volatility as uncertainty indicator, thus limiting its comprehensiveness. Gunnemann, J. (2014) develops national economic policy uncertainty indices, based on newspaper news, for nine European countries, including Portugal, and studies their impact on industrial production and unemployment.

9. See Haddow, A., Hare, C., Hooley, J. and Shakir, T. (2013) and references herein, and the IMF (2012).

10. Other indicators were also addressed, more specifically an application of the approach described by the European Commission (2015), according to which uncertainty indicators were based on the dispersion of replies to opinion surveys of households and enterprises. However, these indicators led to worse results than the economic policy uncertainty indicator for Europe and the composite financial stress indicator and, therefore, are not included in the analysis presented in this Box.

11. Standardised variables were used, i.e. net of the average and divided by the standard deviation computed over the sample period.

12. These were defined on the basis of the cycle’s turning points, corresponding to periods between a peak in GDP and a through prior to the following upturn. The peaks were selected as the quarter that preceded at least two consecutive quarters with negative quarter-on-quarter rates of change of GDP. The troughs in the cycle were identified as the quarter that preceded at least two consecutive quarters during which the quarter-on-quarter rate of change in GDP was positive, following a peak.

13. Models were estimated using the MATLAB-based toolbox presented in Dieppe, A. et al. (2016).

14. Models were estimated with one lag, given that this assumption maximises the model’s likelihood compared with the most common assumption in literature (4 lags), a result that may be related to the relatively low number of observations.

15. See, for instance, Haddow et al. (2013) or European Commission (2015).

16. The structural decomposition of shocks was based on the Cholesky method.

17. For more details on the methodology, see Jarociński, M. and Smets, F. (2008).

18. These results are based on model estimated over the full sample.

19. In 2008 (the onset of the international financial crisis), the financial stress indicator increased by approximately 3 standard deviations, and the economic policy uncertainty indicator increased by 1.5 standard deviations.

IISpecial issue

Life below zero: monetary policy transmission under negative interest rates

37Special issue

Life below zero: monetary policy transmission under negative interest rates

1. IntroductionIn June 2014, the European Central Bank (ECB) took the decision to cross the zero nominal inter-est rate threshold, setting a negative level for the deposit facility rate that remunerates reserves placed by banks in the central bank. This kind of monetary policy, adopted equally by other cen-tral banks, raises new questions for which econ-omists do not yet have definitive answers. If zero is not the effective limit, does a limit exist? What is that effective limit and what are its determi-nants? Is monetary policy transmission with neg-ative interest rates similar to transmission with positive rates? What are the implications for financial system stability?

This Special Issue discusses some of these ques-tions, focusing on monetary policy transmission through the banking system, in a context of zero or even negative interest rates. The article starts by debating what the effective limit on nominal interest rates is and what are its determinants. Next the main transmission channels of mone-tary policy through banks are discussed and the extent to which these change in a negative nom-inal interest rate framework. Finally, a descrip-tion is presented of recent experience in vari-ous economies, focusing on the euro area. Infor-mal observation of developments in bank inter-est rates in the euro area suggests that transmis-sion through banks continues to take place in a similar way to that in a positive rate environment, although the other non-standard monetary poli-cy measures implemented at the same time pre-vent easy isolation of the effects of each meas-ure. Indeed, the different monetary policy meas-ures adopted by the Eurosystem – such as the asset purchase programme, forward guidance, the targeted longer-term refinancing operations, as well as the lowering of key interest rates – interact and contribute to the Eurosystem’s goal of maintaining price stability. For a better

understanding of the contribution of the neg-

ative interest rate policy, an analysis is present-

ed that aims to isolate its effects, although still in

preliminary form, and suggests that there may be

some discontinuity when the zero level of interest

rates is crossed. In other words, there appears

to be a regime shift. However, the analysis does

not offer a conclusion on what the effective low-

er bound is for the monetary policy interest rate.

2. Is zero the effective limit?Until recently, the consensus view was that a lev-

el near zero formed a lower bound on nomi-

nal interest rates. As cash offers a zero nominal

return, it would always be preferred to other less

liquid assets offering negative nominal returns.

Therefore an asset offering a negative nomi-

nal interest rate would not seem sustainable, as

economic agents, including banks, would substi-

tute that asset with cash, which would come to be

used as a preferred saving instrument, alongside

its normal function as a medium of exchange.

In practice, however, holding cash (banknotes

and metal coins) may incur certain costs that

justify the below-zero effective limit on nominal

interest rates, in that the return on cash adjust-

ed for these costs may be slightly negative.

For example, holding high amounts of bank-

notes requires a safe storage facility and possi-

bly insurance and security services. Further-

more, high-value transactions (such as house

purchase) using cash alone are impractical.

Thus there are costs of holding and safeguard-

ing cash that make the effective limit on nominal

interest rates slightly negative. These costs apply

both to individuals and to banks and companies,

although the effective limit may differ according to

the type of economic agent. It is equally likely that

the effective limit differs between economies, as it

depends on several factors, such as the banking


system structure.1 The next section analyses how these factors may influence the effective lower bound on nominal interest rates.

Aside from the different costs and incentives faced by banks, on one hand, and companies and households, on the other, in holding signifi-cant quantities of cash, there may also be institu-tional issues preventing certain nominal interest rates from falling below a certain level. For exam-ple, in some countries, it is illegal to apply nega-tive nominal interest rates to certain bank depos-its. Also, the practical implementation of negative values on interest rates may require the systems in place, such as IT systems, to be adapted.

The issue of the effective limit on nominal inter-est rates has become relevant over the last few years, with central banks adopting addition-al monetary stimulus measures when nominal interest rates have come close to zero. The odd-ity regarding the current situation is the possibil-ity of negative nominal interest rates, since real interest rates (i.e. nominal interest rates adjust-ed for expected inflation) – which are the rele-vant rates for economic agents’ decisions – have reached negative levels several times in the past. In conceptual terms, there is no discontinuity in

the interest rate policy when nominal rates go negative. An expansionary monetary policy con-sists precisely in lowering nominal interest rates with the ultimate goal of reducing real interest rates, irrespective of whether the latter are in negative territory or not. As a result there is no lower bound on real interest rates, which, in cer-tain circumstances, can be strongly negative as there is no upper bound on the inflation rate. By way of illustration, a long series for the interest rate on deposits adjusted for inflation in Portu-gal shows that in the past this rate reached lev-els that were far more negative than those being recorded now (Chart 1). In particular, in the 1970s and 1980s, when interest rates were regulated by law and the inflation rate was very high, the inter-est rate adjusted for inflation reached double-digit negative levels. At the start of the millenni-um, real return on deposits in Portugal was also negative for some time. This suggests that even when the nominal interest rate limit is reached, it would be possible to influence the real inter-est rate if the central bank had instruments that increased inflation expectations. In this case, the discussion about this monetary policy restriction would be less relevant.

Chart 1 • Interest rate (adjusted for inflation) on

household deposits in

Portugal | Percentage

-20

-15

-10

-5

0

5

10

15

1970 1972 1974 1977 1979 1982 1984 1986 1989 1991 1994 1996 1999 2001 2003 2006 2008 2011 2013 2015

Sources: Banco de Portugal and Statistics Portugal.

Notes: Until 1985, interest rates on deposits were regulated by law. Over this period, the nominal rate is assumed to be the legal upper limit, which is generally constant over the year. To account for this lack of variability, the nominal rates over this period are adjusted for the annual inflation rate. From 1985, the monthly year-on-year inflation rate is used. The interest rates on deposits include deposits up to two years. Inflation is measured by the change in the CPI.

39Special issue

Once the zero bound on monetary policy inter-est rates has been crossed, there is still the effec-tive limit discussed previously. Certain proposals have arisen for circumventing this monetary pol-icy restriction. Given that the effective limit exists because economic agents can ultimately choose to hold cash only, these proposals involve discour-aging the use of cash or even eliminating it com-pletely. In modern economies, a significant num-ber of transactions use electronic money. Elimi-nating cash and keeping only electronic money, eliminates the possibility of holding an asset that offers a zero (or slightly negative) nominal return.2 Other proposals allow cash to be kept but estab-lish an exchange rate between it and electronic money. The central bank would provide liquidity in the form of electronic money and could apply negative interest rates to it without restrictions, while cash would continue with a zero return. The exchange rate between the two (with cash more ‘expensive’ than electronic money) would elimi-nate the incentives for agents to hold cash only.3

The next section does not consider these pos-sibilities of eliminating or restricting the cir-culation of cash, and presents a reflection on the way in which decisions on negative mone-tary policy interest rates are transmitted to oth-er interest rates in the economy, with the aim of identifying differences to behaviour under posi-tive policy rates.

3. Is transmission different in negative territory?What does it mean for a central bank to apply negative nominal interest rates? How are these rates transmitted to the banking system and consequently to the rest of the economy? Trans-mission depends on several factors, including the primary factor of the monetary policy imple-mentation framework. Before the financial cri-sis, implementation of monetary policy in the major advanced economies converged towards a system in which the central banks announced a reference interest rate and provided liquid-ity to the banks in order to keep interbank lend-ing rates close to that reference rate. The cen-tral bank’s provision of deposits (reserves) and loans at penalty rates set effective limits on market interest rates. With the financial crisis,

demand for liquidity increased very strongly due to considerations of risk and precaution. At the same time, the central banks followed poli-cies of buying assets (for example, sovereign debt), financed by issuing reserves held by the banks. The system thus changed into one of ample liquidity, in which the central bank takes on a role of greater intermediation in distribut-ing liquidity and the rate of return on reserves constitutes the main benchmark for market interest rates. In this system, a significant num-ber of banks hold a high amount of reserves at the central bank, facilitating the implementation of negative interest rates.

A simple example provides an insight into the way in which transmission takes place in this new monetary policy implementation framework. In this example, the central bank sets the policy interest rate RR which applies to banks’ depos-its in the central bank. The central bank holds the monopoly on issuing banknotes and coins, which have a zero return. These are assumed to be held only by firms and households, which use them in their transactions. Banks take deposits, on which they pay the rate RD, and provide loans at the rate RL. As the central bank does not set restrictions on depositing liquidity into reserves, these work as a last resort for the banks. Thus the policy rate RR functions as a lower bound on the other bank interest rates. If the central bank reduces RR, RL and RD are expected to fall to the same degree. In general, lower lending rates tend to lead to credit being provided to a great-er number of productive projects, helping stim-ulate the economy. On the other hand, more abundant credit may also cause riskier project financing, and, given the increased indebted-ness of the economic agents, an increase in the risk of financial instability in the future.

In this example, it is possible for depositors to substitute deposits with banknotes and coins at no cost, which restricts banks to non-neg-ative rates on deposits. If RR falls below zero, given the restriction on RD, the dynamic of the bank’s balance sheet changes. As there are no restrictions on RL, it can fall below zero, erod-ing the bank’s interest margin and profitability. The bank can adjust its balance sheet to keep the margin constant, providing more loans and


loans to projects with greater risk and expect-ed return. However, there may also be an adverse effect if it increases its lending rate, to offset the loss of margin and the cost of holding reserves. Indeed, the negative rate on reserves may be seen as a tax on a part of the banks’ assets. The banks could possibly try to pass the cost of this tax on to their two types of customers (depositors and debtors) through a decrease in the deposit rate (which cannot be negative) and an increase in the lending rate.

In the example presented, the banks are all assumed to be similar and issues of risks are ignored. In reality, there is heterogeneity, which may lead to banks being affected differently. Also, banks’ structure is far more complex than the example.

A source of heterogeneity between banks relates to their degree of dependence on the central bank. For banks with high reserves – usually the case in euro area countries with better credit rat-ings – the cost imposed by the negative rate on reserves is relatively larger. In contrast, banks with low reserves and greater dependence on the central bank for financing bear a lower cost or may even benefit more from the cheap financ-ing. In this context, the reserve level, aggregate and individual, influences the effects of a negative rate policy differently to those observed under a positive rate regime. Also, the effective lower bound on the policy rate will equally depend on the level and distribution of the reserves. Below that effective threshold, the banks tend to with-draw their reserves from the central bank and start holding cash.

Another factor that influences the transmission of negative rates and the effective limit on the nom-inal interest rate is the structure of the banking market. In a competitive market, lowering policy interest rates would be transmitted to bank lend-ing and deposit rates equally and the effect on the interest margin would be zero. However, in reality, the banks have a degree of market power, which may result in changes in the interest margin.

Aside from these factors influencing the trans-mission of the negative policy rates to the bank interest rates applying to new contracts, this type of policy may have consequences for the banks’ balance sheets and profitability as a result of their

business model. As one of the banks’ main func-tions is the maturity transformation, i.e. obtain-ing short-term financing and offering long-term financing, a flatter yield curve harms the banks’ profitability, as it also happens when there are expectations of low interest rates over a pro-longed period. This effect is common in low-inter-est-rate environments, but may be more acute in the case of negative rates as there is a restric-tion on reducing the rate on deposits. The con-sequences may also differ according to wheth-er loans are variable- or fixed-rate. A bank with a portfolio of predominantly fixed-rate loans ben-efits more from the reduction of interest rates – the more so the greater the maturity of the assets – as its costs fall but its income remains relatively constant. In contrast, a bank with a greater pro-portion of variable-rate loans, as is the case of the Portuguese banks, feels the opposite effect. The effects are not fully symmetrical in the case of an increase in interest rates as generally there is no upper bound on deposit interest rates.4

This analysis suggests that up to a certain lev-el, negative nominal interest rates do not nec-essarily cause difficulties in transmitting mone-tary policy, and this transmission may be similar to that observed under positive nominal inter-est rates. However, there is an effective low-er bound on interest rates, or rather, a level beyond which a reduction in rates has the oppo-site effect to that desired. The factors influenc-ing that effective limit may have a direct effect on transmission to bank rates on new contracts or an indirect effect on bank profitability and financial stability. The limit will be lower (more negative) the greater the proportion of banks’ assets with fixed returns and longer maturities. In contrast, the limit will be higher (less nega-tive) the greater the proportion of short-term variable-rate banks’ assets and the more com-petitive the banking sector, among other factors.

4. Experience with negative policy interest rates

4.1. Implementation and reaction of other nominal interest ratesOver the last few years, central banks in various advanced economies have adopted a regime of

41Special issue

negative monetary policy interest rates (Chart 2).5

The reasons and implementation details differ from central bank to central bank.6 In general, these decisions were motivated by the price sta-bility objective and in the cases of Switzerland and Denmark by exchange rate policy issues too. The central banks of these two countries reduced their respective policy interest rates to substantially negative values (-0.75 per cent) at the start of 2015, to contain the strong appre-ciation prevailing at the time in their curren-cies. Also at the start of 2015, the central bank of Sweden justified lowering its benchmark rate (called repo rate) to negative levels citing risks to nominal stability. At the start of 2016, the Bank of Japan based their negative rate policy on the purpose of achieving the price stability objective as quickly as possible.7

In June 2014, the ECB became the first central bank from a large advanced economy to pass the zero bound on monetary policy interest rates, setting the deposit facility interest rate at -0.1 per cent.8 Since then, this rate has been lowered again on three occasions – September 2014, December 2015 and March 2016 – cur-rently standing at -0.4 per cent. The justification for these decisions was based on the risks to price stability in the euro area. Given the ample provision of liquidity by the Eurosystem, the

deposit facility rate is currently the main refer-ence interest rate.

Since the beginning of the financial crisis, the Eurosystem has adopted a series of accommoda-tive monetary policy measures. From the second half of 2014, these measures were strengthened, with the lowering of the deposit facility rate to negative levels just one example. In parallel, the Eurosystem implemented an expanded asset purchase programme that has been contribut-ing substantially to liquidity provision. In Novem-ber 2016, the portfolio associated with this pro-gramme was worth nearly EUR 1.5 trillion. The Eurosystem also conducted two series of liquidi-ty-providing reverse transactions, with special conditions designed to incentivise the provision of bank credit to the economy. Finally, the ECB has followed a forward guidance policy in which it undertakes to keep monetary policy accom-modative, until a sustained adjustment to the path of inflation, compatible with its price stability objective, is observed. The interaction of these measures, namely the high amount of reserves as a consequence of the purchase programme and the negative deposit facility rate, complicates their separation, both in terms of their classifica-tion and their effects.

The first step in monetary policy transmission takes place through the money markets. The

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

Jan. 12 May 12 Sep. 12 Jan. 13 May 13 Sep. 13 Jan. 14 May 14 Sep. 14 Jan. 15 May 15 Sep. 15 Jan. 16 May 16 Sep. 16

Euro area Denmark Sweden Switzerland Japan

Chart 2 • Monetary policy interest rates | Percentage

Source: Thomson Reuters.

Note: Euro area – deposit facility rate. Denmark – certificates of deposit rate. Switzerland – rate on sight deposits. Sweden – Repo rate. Japan – Rate on excess reserves held at the central bank.


evidence up to now suggests that transmis-sion has functioned in a similar way to that when the official interest rates were at posi-tive levels. The short-term interest rates contin-ued to follow the main reference monetary pol-icy interest rate closely in the five economies (Chart 3). Activity continued in the money mar-ket, although this has fallen significantly over the last few years, as a result of the increase

in credit risk and counterparty risk and cen-tral banks’ increasing intermediation. Long-term interest rates, measured by the 10-year sovereign debt yield, have also followed the official interest rates’ downward movements and the downward revision of monetary policy expectations. Long-term rates are at different levels to policy rates in various economies, which may reflect, among oth-er factors, different monetary policy expectations

Chart 3 • Benchmark interest rates for money and bond markets | Percentage

Switzerland Denmark

-2.0

-1.0

0.0

1.0

2.0

Jan. 14 Jul. 14 Jan. 15 Jul. 15 Jan. 16 Jul. 16

Target interval for the 3-month LIBORSARONPolicy rate3-month LIBOR10-year sovereign debt

-2.0

-1.0

0.0

1.0

2.0


Policy rate Tom-next rate3-month deposit rate 10-year sovereign debt

Sweden Japan

-1.0

0.0

1.0

2.0

3.0


Policy rate STIBOR tom-next3-month STIBOR 10-year sovereign debt

-0.4

0.0

0.4

0.8


Policy rate ON rate3-month TIBOR 10-year sovereign debt

Euro area

-1.0

0.0

1.0

2.0

3.0


Deposit facility Marginal lending facilityMRO rate EONIA3-month EURIBOR 10-year sovereign debt

Source: Thomson Reuters.

Notes: The tom-next rate in Denmark is a 10-day moving average. The 10-year sovereign debt yield for the euro area countries is weighted by the respective GDP weights.

43Special issue

between countries. However, direct observation of the developments in different interest rates does not provide definitive conclusions on the effect of the negative policy rates, as other non-standard monetary policy measures were taken at the same time.

It is also important to know whether the easing in the monetary and financial conditions, result-ing from the lowering of the policy and market interest rates, was reflected also in the bank financing conditions to the rest of the econo-my, in particular in a reduction in bank interest

rates. Direct observation of the developments in bank interest rates suggests that transmis-sion continued in the current regime of negative rates in a similar way to when interest rates were positive. Indeed, the bank interest rates in the countries considered have followed a downward trend in line with reference rates and show some stabilisation recently (Chart 4). However there are differences between coun-tries, in particular in the bank interest margin, which may reflect distinct institutional frame-works and market structures.

Chart 4 • Interest rates on deposits and bank loans | Percentage

Interest rates on time deposits Interest rates on loans

-0.50.00.51.01.52.02.53.03.54.04.5

Jan. 10 Jan. 11 Jan. 12 Jan. 13 Jan. 14 Jan. 15 Jan. 16

Switzerland Denmark Sweden Japan

-0.50.00.51.01.52.02.53.03.54.04.5


Switzerland Denmark Sweden Japan

Interest rates on deposits in the euro area Cost of borrowing to the private sector in the euro area

-1.0

0.0

1.0

2.0

3.0

4.0

5.0


Deposit facility 3-month EuriborEuro area Vulnerable countriesLess vulnerable countries

-1.0

0.0

1.0

2.0

3.0

4.0

5.0


Deposit facility 3-month EuriborEuro area Vulnerable countriesLess vulnerable countries

Source: ECB, Swiss National Bank, Thomson Reuters and Banco de Portugal calculations.

Notes: New business interest rates.

Denmark and Sweden – weighted average rate of deposits with agreed maturity from non-financial corporations and households; weighted average rate of loans to non-financial corporations and households for house purchase, consumption and other purposes (three-month moving average in the case of Denmark).

Switzerland – rate on three-month time deposits with an amount equal to or greater than 100,000 francs; weighted average rate of mortgage and investment loans.

Japan – average rate on one-year time deposits with an amount equal to or greater than 10 million yen; average rate on loans from domestic banks.

Euro area – Average interest rate of overnight deposits, deposits with agreed maturity and deposits redeemable at notice from households and non-financial corporations, weighted by their outstanding amounts; cost of borrowing to the private sector calculated based on average interest rates on loans to non-financial corporations and households for house purchase, weighted by a 24-month moving average of the new business amounts.


In the euro area, bank interest rates generally followed the trend in the Euribor. Between June 2014 and September 2016, the Euribor rate fell over 50 b.p., deposit rates over 40 b.p. and lend-ing rates around 100 b.p., with these variations more pronounced in the euro area countries most affected by the financial crisis. As the down-ward trend continued in the last few months, one conclusion could be that transmission con-tinues to take place and that there is no evidence of adverse changes in terms of restrictions on credit conditions. The interest rate on deposits did not reach negative levels, although the val-ues presented may be an upper limit on the true return for the depositor as bank commissions are not included. However, keeping the nega-tive rate policy for a prolonged period increas-es the risk of unintentional effects. There are also other factors – among them the adoption of other non-standard monetary policy measures – which may have influenced developments in bank interest rates. To take more robust conclu-sions on the effect of the negative interest rates, another approach should be taken that isolates the different effects. The next section presents a preliminary analysis in this regard.

4.2. An econometric analysis of transmission to bank interest rates in the euro area

Given the uncertainties discussed above, it is particularly interesting to understand whether transmission to bank interest rates in the euro area in a negative rate environment differs from what happens in a positive rate environment. In normal times, bank rates tend to follow a bench-mark interest rate, generally a short-term Euri-bor, although to a differentiated degree accord-ing to the type of contract. For example, the interest rate on sight deposits tends to be the lowest deposit rate given the high liquidity. Fixed interest rate loans tend to feature interest rates with lower variability over time and at levels clos-er to market interest rates for longer maturi-ties. In some countries, including Portugal, the Euribor serve normally as an index for most loan contracts, meaning that the rates on loans tend to follow Euribor’s developments closely.

To study monetary policy transmission, an econo-metric analysis was undertaken based on individ-ual information for a representative sample of euro area banks, for the period between August 2007 and September 2016.9 The data used allow to explore bank level heterogeneity, following a panel estimation approach with fixed effects at bank level.10

Below is the model estimated, in which the indi-ces

11

pré‐aviso de famílias e empresas não financeiras, ponderadas pelos montantes vivos. Custo de financiamento do setor privado calculado com base nas taxas de juro médias dos empréstimos às empresas financeiras e às famílias para compra de habitação, ponderadas por uma média móvel de 24 meses dos montantes dos novos empréstimos.

4.2 Uma análise econométrica à transmissão às taxas de juro bancárias na área do euro

Tendo em conta a dificuldade em fazer uma avaliação precisa e isolada dos efeitos das taxas de juro negativas, importa contudo perceber como se tem efetuado a transmissão desta medida, em particular ao mercado bancário. Dadas as incertezas acima discutidas, é de especial interesse perceber se a transmissão às taxas de juro bancárias na área do euro em ambiente de taxas negativas difere do que acontecia anteriormente. Em tempos normais, estas taxas deverão seguir uma taxa de juro de referência, geralmente a taxa de juro de curto prazo Euribor. A proximidade com que seguem a taxa de referência depende do tipo de contrato. Por exemplo, uma taxa de juro de depósitos à vista tende a ser sempre mais baixa, dada a elevada liquidez. Empréstimos com taxa de juro fixa tendem a apresentar taxas de juro que variam menos ao longo do tempo, estando mais próximas de taxas de juro de mercado de mais longo prazo. Em alguns países, incluindo Portugal, as taxas de juro Euribor costumam servir de indexante a grande parte dos contratos de empréstimos, o que significa que as duas taxas de juro têm um elevado co‐movimento.

Para melhor responder à questão, é realizada uma análise econométrica com base em informação individual de uma amostra representativa de bancos da área do euro.8 O período para o qual existem dados disponíveis e sobre o qual incide a análise começa em agosto de 2007 e termina em setembro de 2016. Esta base de dados permite então explorar a heterogeneidade existente ao nível dos bancos, seguindo‐se uma abordagem de estimação de painel com efeitos fixos ao nível do banco.9

Apresenta‐se de seguida o modelo estimado, em que os índices j, c e t representam, respetivamente, o banco j, o país c e o mês t, e incluem variáveis de controlo de país e banco e são efeitos fixos de banco:

Visto que o objetivo é identificar uma alteração na transmissão da política monetária, devido à passagem para a política de taxas negativas, nas taxas ativas e passivas praticadas pelos bancos, utilizam‐se como variáveis dependentes taxas de juro médias ponderadas pelos respetivos

8 É utilizada uma base de dados confidencial do Eurosistema para uma amostra representativa de bancos da área do euro com o mesmo tipo de informação que se encontra pública ao nível agregado para a área do euro e para os países no contexto das estatísticas monetárias e financeiras e das estatísticas das taxas de juro das instituições monetárias e financeiras. Para mais informação sobre estas estatísticas, veja‐se https://www.ecb.europa.eu/stats/money/aggregates/aggr/html/index.en.html e https://www.ecb.europa.eu/stats/money/interest/interest/html/index.en.html. 9 Dado que as principais variáveis de interesse são agregadas ao nível da área do euro e dado que grande parte das variáveis de controlo são agregadas ao nível de país, o cálculo dos erros‐padrão é agrupado por país. A nota associada ao Quadro 1 apresenta uma descrição de todas as variáveis utilizadas.

,

11








and

11








respectively represent bank

11








,, country c and month

11








,

11








and

11








include control variables by country and bank and

11








corresponds to fixed effects by bank:

11








11








11








As the goal is to identify whether there is a change in the transmission of monetary policy to lending and deposit rates practiced by the banks, in a negative rate environment, the aver-age interest rates weighted by their respective amounts of new loans and new deposits are used as dependent variables (

11








). The rate on deposits relates to households’ and non-financial corporations’ deposits with agreed maturity and the rate on loans includes loans to non-financial corporations for the various maturities and to households for house pur-chase, consumption and other purposes. Since new business interest rates are used, the anal-ysis does not provide answers to questions regarding the impact on the banks’ balance sheet, namely regarding profitability.

As mentioned above, bank interest rates tend to follow the Euribor. The aim of including this iso-lated variable in the regression is to draw con-clusions about the effect of changes in Euribor on the bank interest rates (given by the coef-ficient

11








).To capture the effect of the shift to a negative interest rate policy, the DFR variable is included, which assumes the absolute value of the deposit facility interest in periods in which this is below zero. The main variable of interest is given by the interaction between the Euribor and

45Special issue

the level of the deposit facility rate (DFR*Euribor).

A coefficient with an opposite sign to the Euri-

bor coefficient sign suggests that in a negative

rate environment, transmission of monetary pol-

icy to financing conditions for agents is mitigated.

Indeed, the results of the regressions present-

ed in Table 1 suggest precisely this attenuation

effect of monetary policy transmission in most

cases. The Euribor coefficient is positive, which

suggests that effectively the bank interest rates

follow the benchmark interest rate. The shift to

a negative interest rate regime (captured by the

DFR variable) also contributed to the fall in the

interest rates on loans. However, bank interest

rates’ sensitivity to Euribor fell in this new regime,

and may even reverse the effect of transmission

via Euribor to the extent that the deposit facility

rate falls to more negative levels. There seems to

be evidence therefore in support of discontinu-

ity between the two policy interest rate regimes,

above or below zero. This result suggests that

there is a value beyond which further decreases

in the policy interest rates may have the oppo-

site effect to that intended. However, it does not

provide a conclusion on what that limit might

be, although the absence of strong disruptions

in economic agents’ behaviour suggests that the

limit has not yet been reached. Even so, the risk

remains that the maintenance or expectation of maintenance of negative policy rates over a pro-longed period changes agents’ incentives, lead-ing to a reversal in behaviour.

Other factors were included in the regressions presented above which influence the bank inter-est rates but that are not related with transmis-sion of monetary policy interest rates. Firstly, het-erogeneity at bank level partly reflects geograph-ical heterogeneity, such that some of the effects should be expected to depend on regional fac-tors. Control variables by country were there-fore included in the regression (

11








). These variables are intended to control for factors like fragmentation of the euro area, which involved a strong dispersion of the bank interest rates at the peak of the sovereign debt crisis, or for the position in the economic cycle, which may dif-fer between countries. Furthermore, to control for the effect of the other monetary policy meas-ures adopted at the same time by the Eurosys-tem, variables were included by country, such as the level of targeted longer-term refinancing operations or the long-term interest rates, which fell following the asset purchase programme.11 Some variables by bank were also included in the analysis which influenced the structure of the bank’s balance sheet (

11








).

Table 1 • Policy rate transmission to bank interest rates: results on the main variables of interest

Interest rate on deposits Interest rate on loans

DFR t 0.041 -0.363Euribor t-1 0.132 0.215DFR t * Euribor t-1 -0.414 -0.775

No. observations 16,536 14,162R2 0.935 0.891No. of banks 209 187

Notes: Panel-data estimates with fixed effects at bank level for the weighted average interest rate on deposits with agreed maturity from non-financial corporations and households and for the weighted average interest rate on new business loans to non-financial corporations and households. Independent variables considered and presented in the table: DFR designates the absolute value for the interest rate on the deposit facility when this is negative and zero otherwise; Euribor designates the three-month Euribor interest rate. An autoregressive term was included in each equation which is not reported in the table. Control variables set at country level (Xct-1 in the equation) and not reported: 10-year sovereign debt yield; balance of the TARGET payment system as a percentage of banking system assets; total amount placed in targeted longer-term refinancing operations as a percentage of banking system assets; unemployment rate. Control variables set at bank level (Yjct in the equation) and not reported: deposits as a percentage of total main assets; 'capital and reserves' item as a percentage of total main assets; loans to non-financial corporations as a percentage of total main assets; new business loans with variable rate or with fixed maturity up to one year as a percentage of total new loans; deposits considered for calculating M3 as a percentage of total deposits; log of total main assets. The signs on the coefficients are in line with what would be expected. Standard errors were clustered by country. The coefficients with 5 per cent significance are in bold.


Economic research on the transmission of neg-ative interest rates is still at a very early phase, as this is a relatively recent phenomenon. Aside from the effects through bank interest rates, for which a preliminary analysis has been present-ed here, it is very important to understand the effects through quantities. The evidence availa-ble suggests that in a negative interest rate envi-ronment, the euro area banks tend to expand credit more and increase their holdings of non-domestic sovereign debt securities.12 Howev-er, these effects only take place in banks locat-ed in less vulnerable countries and are strong-er the larger the liquidity surplus held by the bank. The banks with greater excess reserves are more directly penalised by the ‘tax’ effect of the negative interest rate on reserves, thus are those which have greater incentive to find alternative investments for those funds. Anoth-er study concludes that the negative interest rate environment in the euro area was related to an increase in risk-taking by the banks.13 This behaviour is more accentuated in banks with lower capital ratios and depends on the banks’ financing structure, with the effect stronger in banks where deposits have greater importance. These results suggest that the restriction on the deposit rates assuming negative values may be key for the banks that depend the most on this financing source.

5. Final considerationsRecent experience in the euro area and in oth-er economies shows that zero is not in fact an effective lower bound on nominal interest rates. As discussed in this Special Issue, there are rea-sons that justify the existence of a below-zero lim-it, but this could differ between economies due to various factors, such as the banking system’s characteristics. The limit may also differ between banks, firms and households. However, knowl-edge about these factors and the transmission mechanism of monetary policy in very low inter-est rate environments is still at a very early stage.

According to the preliminary evidence present-ed here, transmission of monetary policy may

present different characteristics in negative or positive nominal interest rate environments. Although there is no evidence that the lower bound on interest rates in the euro area has been crossed, the transmission effects seem to be smoothed compared to those observed in a positive interest rate paradigm. However, it is difficult to isolate the effects of the negative policy interest rates from those of other mon-etary policy measures adopted at the same time by the Eurosystem. Although the different measures contribute over time to achieving the price stability objective, the risk remains that maintenance or expectation of maintenance of the negative policy rates for a prolonged peri-od creates the opposite effect to that intended.

In this Special Issue, issues of financial stabil-ity that may arise from low-nominal-interest-rate environments were not discussed. In par-ticular, this environment may present difficul-ties for banks’ profitability, may incentivise an increase in risk-taking by the financial institu-tions and may present difficulties to specific types of investors with longer term commit-ments, like insurance companies or pension funds. These are some examples of addition-al uncertainty factors associated with keeping nominal interest rates negative which may jus-tify a cautious approach in following this type of policy over a long period.

47Special issue

Notes1. Brunnermeier, M. and Y. Koby (2016), 'The ‘reversal interest rate‛: An effective lower bound on monetary policy', mimeo.

2. On this proposal, see Rogoff, K. (2016), The Curse of Cash, Princeton University Press and Goodfriend, M. (2000), 'Overcoming the Zero Bound on Interest Rate Policy', Journal of Money, Credit and Banking, vol. 32(4), pages 1007-35, November.

3. Agarwal, R. and M. Kimball (2015), 'Breaking Through the Zero Lower Bound', IMF Working Papers 15/224.

4. In regard to the effect of the negative rate environment on bank profitability, see Financial Stability Report, Banco de Portugal, May 2016, for example.

5. The central bank of Hungary also set the overnight deposit facility interest rate at a slightly negative level (-0.05 per cent) from March 2016.

6. To reduce the potentially negative impact of this policy on bank profitability, some central banks chose to introduce exemption systems in tiers for reser-ves. The central bank of Denmark offers certificates of deposit at the current interest rate of -0.65 per cent, while it accepts deposits at a zero rate of return. There are individual quantitative limits on deposits accepted, above which the funds are converted into certificates of deposit. Currently, the National Bank of Switzerland applies a rate of -0.75 per cent on sight deposits above a set individual limit, calculated based on minimum reserve requirements. The Bank of Japan divides the remuneration of the reserves into three tiers, currently -0.1 per cent, 0 per cent and +0.1 per cent. In the euro area, reserve require-ments are remunerated at the main refinancing operations rate (currently 0 per cent) and the excess reserves at the deposit facility rate (-0.4 per cent).

7. For more information, see: Bech, M. and A. Malkhozov (2016), 'How have central banks implemented negative policy rates?', BIS Quarterly Review, March 2016, and Ball, L., J. Gagnon, P. Honohan and S. Krogstrup (2016), What Else Can Central Banks Do?, Geneva Reports on the World Economy 18, CEPR.

8. The Eurosystem sets three key interest rates in a corridor system: the main refinancing operations rate and the deposit facility and lending facility rates. The facilities interest rates establish a lower and an upper bound respectively on market interest rates. The banks' reserves placed in the central bank that exceed the minimum reserve requirement are remunerated at the deposit facility rate.

9. A confidential database belonging to the Eurosystem was used which includes individual information for each bank, similar to published aggregate--level information for the euro area and for countries, in the context of the monetary and financial statistics and monetary financial institutions interest rate statistics. For more information on these statistics, see https://www.ecb.europa.eu/stats/money/aggregates/aggr/html/index.en.html and https://www.ecb.europa.eu/stats/money/interest/interest/html/index.en.html.

10. As the main variables of interest are aggregated at euro area level and most of the control variables are aggregated at country level, standard errors are clustered at the country level. Table 1 presents a description of all the variables used.

11. However, the analysis would ideally control for the effect of these measures at bank level, but that information is not available.

12. Demiralp, S., J. Eisenschmidt and T. Vlassopoulos (2016), 'The impact of negative rates on bank balance sheets: Evidence from the euro area', mimeo.

13. Heider, F., F. Saidi and G. Schepens (2016), 'Life below zero: Bank lending under negative policy rates', mimeo.

https://www.ecb.europa.eu/stats/money/aggregates/aggr/html/index.en.html

https://www.ecb.europa.eu/stats/money/interest/interest/html/index.en.html

https://www.ecb.europa.eu/stats/money/interest/interest/html/index.en.html

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