Firm performance and the business environment: Where we are and future directions

Sabancı UniversityCompetitiveness Forum (REF)

March 27, 2015

Alvaro S. González and Can SelçukiTrade and Competitiveness Practice

Group

The roadmap

Motivation to study the relationship between the business environment and firm performance;

A literature review; Macro approach Micro approach

Lessons from literature review;

Unsolved conundrums in firm performance, allocative efficiency and markets; and

Research plan going forward.

MOTIVATION, DEVELOPMENTS AND ASSUMPTIONS

Recent developments in research on firm performance and the business environment

A number of studies analyze the impact of the business climate variables on different dimensions of firm performance;

These assume that… institutional features of an economy can affect the performance of

firms; institutional features vary widely across and within countries; and firms facing better business environments are expected to perform

better.

Significant theoretical and empirical literature support these assertions.

LITERATURE REVIEW

Literature – Cross-country institutional quality and macroeconomic performance (1)

Cross-country data to relate broad indicators of institutional quality, policy and infrastructure to macroeconomic outcome variables—GDP per capita (Acemoğlu, Johnson and Robinson, 2001), GDP per worker (Hall and Jones, 1999), growth rates (Knack and Keefer, 1995 or Mauro, 1995).

On infrastructure... Aschauer (1989) finds that it has a large impact on aggregate

total factor productivity; and Calderón, Moral-Benito, and Servén (2010)—covering 88

countries and spanning the years 1960–2000—find statistically (and economically) significant estimates of the output contribution of infrastructure.

Literature – Cross-country institutional quality and macroeconomic performance (2)

On institutions and the policy environment… Using five-year panel of data from the Doing Business indicators,

Eifert (2009) finds evidence that regulatory reforms lead to higher aggregate investment rates (roughly, factor demand) or GDP growth conditional on investment rates (roughly, factor productivity) in countries which are relatively poor (conditional on governance) and relatively well-governed (conditional on income); and

Dollar, Hallward-Driemeier and Mengistae (2005) find long-run growth is faster in countries with higher quality legal institutions, better law enforcement, increased protection of private property rights, improved central government bureaucracy, smoother operating formal sector financial markets, increased levels of democracy and higher levels of trust.

Concerns about the robustness of these results.

Endogeneity between infrastructure, institutional quality on long-run economic development may be product of:

measurement errors stemming from the use of public capital figures as proxies for infrastructure (Straub, 2010) and institutional quality;

omitted variables, arising when a third unobserved variable that affects infrastructure, institutions and growth measures; and

changes in institutional quality, infrastructure outlays and productivity or output might be simultaneously determined.

Instruments used, such as geographical or historical preconditions (latitude, colonial history, settler mortality, etc.), limit the ability of empirical models to identify consequences of institutional change on growth; and

In addition, aggregate business climate indicators are often imprecise because they rely on de jure information or subjective judgments.

Micro approaches–competition and regulation

Competition and entry should promote efficiency and prosperity (Aghion and Griffith 2005);

Carlin, Schaffer and Seabright (2006) show that anti-competitive practices (as well as tax rates and tax administration, access to and cost of finance, and policy uncertainty and macroeconomic stability) are the most important business constraints in all countries;

Competition has significant positive impact on productivity, explaining more variation in enterprise performance than infrastructure; and

Bastos and Nasir (2004), Escribano and Guasch (2005), Beck, Demirgüç-Kunt and Maksimovic (2005), Hallward-Driemeier, Wallsten and Xu (2006) and Commander and Svejnar (2007) include measures of competition in business climate regressions.

Micro approaches–regulation and firm-level performance

Beck, Demirgüç-Kunt and Maksimovic (2005) find that the “degree of legal obstacles” negatively affect enterprise productivity but regulation does not necessarily have a negative effect—and has a positive effect when it is consistently enforced;

Aterido and Hallward-Driemeier (2007) and Aterido, Hallward-Driemeier and Pagés (2007)—consistent enforcement of regulations positively correlated with employment growth in most developing countries, particularly marked for small firms—though not significant for Africa;

Both papers also obtain a generally positive effect of management time spent dealing with authorities, which they interpret as representing the benefit from obtaining public goods. On the other hand, pure red tape—for example unnecessary delays in customs—has a significant negative effect; and

Endogeneity of input choices may bias results directly (as for labor in Aterido, Hallward-Driemeier, and Pagés 2007) or indirectly if it affects productivity (as in Escribano and Guasch 2005).

Micro approaches–financial constraints and firm-level performance

Within countries, enterprise size appears to be determinant as it influences the ability of obtaining credit from banks (Beck, Demirgüç-Kunt and Maksimovic, 2005);

Even after controlling for a country’s institutions, smaller firms report significantly higher financial obstacles than large firms (Ayyagari, Demirgüç-Kunt and Maksimovic, 2008);

Aterido, Hallward-Driemeier and Pagés (2007) find that smaller firms have significantly less access to different forms of finance, controlling for age, export status, ownership and industry. Small firms finance a lower share of investments with formal credit;

Bigsten and Söderbom (2006) show that close to two-thirds of microfirms, but only 10 percent of large firms, are credit constrained in sample of African countries; and

Within countries, access to finance is particularly problematic for less productive firms (Carlin, Schaffer, and Seabright 2006); and

However, results are not always straightforward…

Commander and Svejnar (2007) find no significant effect from subjective ‘cost of finance’ variable on firm revenue Eastern Europe and Central Asia firm-level data; and

Dollar, Hallward-Driemeier, and Mengistae (2005) find no significant effect of the indicator ‘access to overdraft facility’ on productivity of firms in the garment industry, but in an expanded sample find a significant and strongly positive effect on annual sales growth.

Micro approaches–corruption, crime and firm-level performance

Crime and corruption show up as important constraints in all country groups except the OECD, with crime a constraint in 25 percent of countries and corruption in 70 percent (Carlin, Schaffer and Seabright, 2006);

Escribano and Guasch (2005) find that firms suffering more from crime incidents have lower productivity;

Escribano and Guasch (2005) also find where firms can afford to pay more bribes they tend to be more productive in the first place, reap productivity advantages from their payments, or both.

Fisman and Svensson (2007) find a “strong, robust, and negative relationship between bribery rates and the short-run growth rates of Ugandan firms, and . . . the effect is much larger than the retarding effect of taxation.”;

Aterido, Hallward-Driemeier and Pagés (2007) find a significantly negative effect of corruption on the growth of small, medium, and large firms but a significantly positive effect for microfirms;

Hallward-Driemeier, Wallsten and Xu (2006) find that reducing the mean score of corruption by one standard deviation has a positive effect on sales growth by 6 percent. However, no significant effect of corruption on productivity and employment growth;

Beck, Demirgüç-Kunt and Maksimovic (2005) regress sales growth on corruption indicators and find no statistical significance; and

Bastos and Nasir (2004) find rent predation (a combination of corruption and regulation) has a significantly negative effect, but explains less productivity variation than infrastructure and competition measures.

Lessons learned…what is left out?

Firm choices on formality or informality Rauch (1991), Straub (2005), or De Paula and Sheinkman (2008), together with tools from industrial organization and contract theory good basis for formalizing insights on market behavior in developing countries;

What about differences between ‘deals vs. rules’ and uncertainty (Hallward-Driemeier, Khun-Jush and Pritchett, 2010)?;

Look at the speed of adjustment? The relationship between business environment and when inflection points happen during business cycles;

Instead of firm performance, or sectors, are not allocative efficiencies a more relevant measure?; and

What about markets? If business environment can affect firms, it surely affects markets.

NEW APPROACHES—LESS FIRMS, MORE MARKETS

Firm growth and employment and annual turnover (Turkey vs. ECA economies)

Turkey firms start out fewer workers but end up more than average as they grow.

2

3

4

5

6

log

of

age

1 2 3 4 5 6log of labor

95% CI Turkey Other ECA Countries

Source: Author's estimation using World Bank's Enterprise Survey data.

age predicts size of labor force

Turkey vs. Other ECA Countries

The opposite is true when looking at annual turnover.

10

15

20

25

30

log

of

age

10 15 20 25 30log of sales

95% CI Turkey Other ECA Countries

Source: Author's estimation using World Bank's Enterprise Survey data.

age predicts sales revenue

Turkey vs. Other ECA Countries

Firm growth and employment and annual turnover (Turkey vs. High-income developing economies)

Relationship between age and labor force consistent when comparing Turkey to high income economies.

10

15

20

25

log

of

age

10 15 20 25log of sales

95% CI Turkey High Income Developing Countries

Source: Author's estimation using World Bank's Enterprise Survey data.

age predicts sales revenue

Turkey vs. High Income Developing Countries

Same here….

2

3

4

5

6

log

of

age

1 2 3 4 5 6log of labor

95% CI Turkey High Income Developing Countries

Source: Author's estimation using World Bank's Enterprise Survey data.

age predicts size of labor force

Turkey vs. High Income Developing Countries

We are familiar with the Hsieh-Klenow (2009) misallocation results….

What does misallocation look like in Turkey? (TFPR)

0

.05

.1

.15

.2

.25

den

sity

0 10 20 30total factor productivity

Turkey 2008 Middle Income Economies

Source: Author's estimation using World Bank's Enterprise Survey data.

kernel density of TFP

Turkey 2008 vs. MIC Economies

0

.05

.1

.15

.2

den

sity

0 10 20 30total factor productivity

Turkey 2013 Middle Income Economies

Source: Author's estimation using World Bank's Enterprise Survey data.

kernel density of TFP

Turkey 2013 vs. MIC Economies

Misallocation in Turkey’s food processing and garment sectors less than in Brazil and Mexico.

Misallocation in the food processing sector is relatively less then in Brazil or Mexico…

The same, but even more so, in the garments sector

0

.05

.1

.15

.2

.25

dens

ity

5 10 15 20total factor productivity

Turkey Brazil Mexico

Source: Author's estimation using World Bank's Enterprise Survey data.

kernel density garments TFP

Turkey vs. Brazil, Mexico

0

.05

.1

.15

.2

dens

ity

5 10 15 20 25total factor productivity

Turkey Brazil Mexico

Source: Author's estimation using World Bank's Enterprise Survey data.

kernel density food processing TFP

Turkey vs. Brazil, Mexico

What about markets?…persistent misallocations bring forth questions about the efficiency of markets.

How is it that low productivity firms survive?;

This goes beyond just competition…is there segmentation in markets?; and

How and why does this segmentation persist?

Rationale for looking at the micro-patterns of markets and their determinants…

Proper functioning of

markets is essential for

optimal resource allocation;

Optimal allocation of resources is critical for

productivity growth; and

Inaccurate, unclear price

signals distort the allocation of

resources and stunt productivity

growth.

21

Literature review – factors associated with inefficient markets.

•Distance and/or topography•Poor infrastructure•Language, ethnic, political or cultural networks•Information problems – commodity-, consumer,-or location-specific

Isolation

•Variability in thickness on supply side•Variability in thickness on demand side•Market power•Risk aversion – symptom or characteristic?•Characteristic of goods – price elasticities, menu costs, information costs, quality•Economic density (dollars per square meter)

Market structure

•Distortion of prices or quantities•Restrictions to entry and/or competition•Poor regulation, consumer protection, and/or competition enforcement•International borders and informal trade

Policies

•A lack of forward markets (no smoothing)•A lack of product standards or guarantees (few arm’s length transactions)•Poor access to finance (little smoothing and arbitrage)

Institutions

22

Measures of market efficiency – markets are efficient when they reflect all new or existing information.

Segmentation and market integration:

• Variance decomposition into national, sub-national and idiosyncratic factors

• Price differentials between international and domestic markets

Dispersion:• Relative standard deviation by

market

Volatility:• Frequency of observations

statistically different from trend-adjusted mean

• Relative standard deviation across time

Pass-through:• Magnitude• Speed (delays)

23

Here is what we propose…

Step 1: Estimate indicators to characterize the performance of markets. a) Markets are defined by commodity-location pairs; and

b) Performance is defined by efficiency of markets.

Step 2: Identify and understand factors and determinants correlated with indicators’ variation across markets.

24

ÇOK TEŞEKKÜRLER!