Economic Development and Satellite Images

Paul A. Raschky

joint work with Roland Hodler

SOAP Collective, April 09, 2016

1 / 22

Introduction

I Some political leaders choose policies that mainly benefitpeople in their preferred region.

I We call this phenomenon regional favoritism, and see it as aform of rent seeking and, in some cases, corruption.

2 / 22

Country example

Zaire (now DRC):

I Mobutu was dictator of Zaire from 1965 to 1997.

I He had an estimated fortune of $5 billion and relied on the“diversion of Zairean government funds, embezzlement ofexport earnings, and the massive diversion of foreign loans andaid” (Edgerton 2002).

I He was born near his ancestral home Gbadolite, a remotetown in Northern Zaire, where

I he built a huge palace complex costing $100 million, luxuryguesthouses and hotels, and an airport capable of handlingsupersonic Concordes.

I he set up the country’s best supply of electricity, water, phonelines, and medical services.

3 / 22

Country examples

Zambia:

I Presidents are expected “to favor members of their ethnicgroup when making government appointments,” and “tochannel donor aid or relief food to their regions” (Posner2005).

Bolivia:

I Evo Morales is the first indigenous president, and the firstpresident from a rural district in the highlands.

I He uses natural resource revenues from the lowlands andother government revenues to support the poor indigenouspopulation in the highlands.

I In his birth district Orninoca (less than 2,000 inhabitants),he built a modern sports stadium for 5,000 spectators andannounced the construction of a museum costing $5 million.

4 / 22

Research Question

I Research Questions:

1. Do political leaders across the globe systematically choosepolicies that favor people in their preferred region?

2. How does the extent of such regional favoritism depend onpolitical institutions and windfall gains, such as oil rents (orforeign aid)?

I Challenge:I How can we measure political favouritism with official

macroeconomic data that is provided by the governments?I Analyzing regional favoritism, requires subnational data on

economic activty. This data does not exist for many (lessdeveloped) countries and is often of poor quality.

5 / 22

Data

Nighttime light data:I NOAA provides annual nighttime light data for 1992–2009:

I US Air Force weather satellites circle the earth 14 times eachday and record light intensity.

I Readings of light intensity every evening (8.30–10.00pm) in thedark half of the lunar cycle in seasons when the sun sets early.

I Scale from 0–63 for pixels of about 1 km2.

I Like GDP, nighttime light is a proxy for economic activities.I Most forms of consumption and production in the evening

require light, and public infrastructure is often lit at night.

I Unlike GDP data, nighttime light data is availableI in the same high quality for all countries,

I at the local level, making it “uniquely suited to spatial analysesof economic activity” (Henderson et al. 2012).

6 / 22

DataI Illustration: Nightime light intensity in Gbadolite

1992 1996

1998 2003

7 / 22

Data

I Our indicator for economic activity average is nighttime lightin every subnational region, country, and year in our sample.

I To construct this indicator, we useI GIS (Geographic Information System) raster files of average

annual nighttime light,

I GIS-shapefile with information on subnational boundaries (ofthe lowest federal level available for each country).

8 / 22

Satellite data of nighttime lights and boundaries - India2000

9 / 22

Data

Leaders data:

I The data base of Goemans et al. (2009) identifies the effectivepolitical leader of each country for many years up to 2004.

I We update the data base to 2010 and add the birthplaces ofall political leaders (from 1990 onwards).

I We exclude leaders born abroad or without birthplaceinformation.

I We use GIS to map the leaders’ birthplaces with subnationalregions.

10 / 22

Data

I Our final dataset consists yearly observations for 38,450regions in 126 countries from 1992 to 2009 using data fromvarious sources:

I Satellite data on nighttime light intensity, which is a measureof economic activity available for any region in any country.

I Data on the country’s political leaders and their birth places.

I Data on political institutions (level of democracy), oil rentsand foreign aid.

11 / 22

Summary of Results

I We show that regions have more intense nighttime light whenbeing the birth region of the current political leader,

I we argue that this finding provides evidence for widespreadregional favoritism, and

I we show that weak political institutions promote regionalfavoritism, and that these effects are economically significant.

I Back of the envelope calculation:

I Being the leader region of a weakly institutionalized countryincreases regional GDP by 8%.

I This effect becomes even larger in weakly institutionalizedcountries that receive large oil rents or large aid inflows.

12 / 22

Are the Effects of Regional Favoritism Sustainable?

13 / 22

Other Projects

14 / 22

The Role of the Media in Asymmetric Warfare

Date: 17/09/2008 Cause of death: IEDMedia Coverage: ABC 10 sec.

Date: 24/02/2009 Cause of death: IEDMedia Coverage: ABC 20 sec.; CBS 20 sec.; NBC 10 sec.

I On September 16th 2008, the U.S. FED announces the USD85 billion bail-out for AIG.

15 / 22

The Role of the Media in Asymmetric Warfare

I This paper compiles a dataset from various sources:

I ’Leaked’ U.S. military logs about the war (insurgency) inAfghanistan.

I Logs contain around 90,000 events of military relevance. Dailydata from 1/1/2004 - 31/12/2009.

I Media attention: Daily U.S. media data on reports aboutAfghanistan.

I Index on daily news pressure (Availability of newsworthyevents).

I (Yearly) Satellite data on nighttime light intensity.I Proxy for military/economic importance of an area in

Afghanistan.

I Spatial information about mobile phone coverage inAfghanistan.

16 / 22

Economics of Technology

I Joint project with Simon Angus and Klaus Ackermann (bothMonashU)

I A trillion observations to infer socio-economic behavior.

17 / 22

Economics of Technology

Daily internet activity & Oyster-Card Intensity, London GB

Day of the Weekmon tue wed thu fri sat sun

Varia

tion

in IP

Act

ivity

,C

omm

uter

Act

ivity b

b Lunch peak, 12.45pm Mon-Thur, 1.15pm Fri, 3.15pm Sun

a

a Pre-commute/Wake-up peak, 4.45-5am Mon-Thu (absent Fri), 5.30am Sat

c

c Late-evening peak, 8.45-9pm Mon-Thur, 9.30pm Fri, 9pm Sat & Sun

d

d Early-evening peak, 6–6.15pm Tue-Sat, 6.45pm Sun (indistinct Mon)

18 / 22

Economics of Technology

Religion: Stated vs. Revealed Behavior: Jerusalem vs. Tel Aviv

19 / 22

paul.raschky@monash.edu

20 / 22

APPENDIX

21 / 22

Data

Other data:I Democracy: Polity2 score from the Polity IV project.

I It is the difference between the democracy and the autocracyscore.

I It measures constraints on the executive, the competitivenessand regulation of political participation, and the openness andcompetitiveness of executive recruitment.

I We rescale it so that it ranges from 0 to 1, with higher valuesimplying better political institutions.

I Foreign Aid: Official net development assistance (ODA) incurrent USD per capita from DAC OECD.

I Oil rents: Oil rents per capita from the World Bank’s adjustednet savings data base.

I Oil rents are calculated as oil production times the differencebetween the world market price of oil and extraction costs.

22 / 22