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Geography and Labor Market Performance

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Abstract

Using data from 76 countries and a large number of controls, this paper analyses how geographical characteristics affect labor market performance. We find that different geographical characteristics have very different effects. While a larger share of highly fertile soil appears to lower employment and increase unemployment, more abundant mineral resources seem to increase employment without affecting unemployment. A larger share of tropical area is associated with higher employment and lower unemployment rates. Neither proximity to the ocean, or to ocean-navigable rivers, nor elevation appears to affect labor market outcomes.

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Notes

  1. For a survey of the theoretical literature, see Isham et al. [2005]. Empirical studies support the “natural resource curse” hypothesis, finding that mineral-rich economies grow slower [e.g., Sachs and Warner 1995; Sachs and Warner 2001; Leite and Weidmann 2002; Bravo-Ortega and de Gregorio 2007].

  2. As the correlation matrix also indicates, there is no substantial correlation among our main geographical variables (Appendix C).

  3. Examples of studies on economic growth using the variable “latitude” include Sala-i-Martin [1997], Bloom and Sachs [1998], Acemoglu et al. [2001], and Rodrik et al. [2004].

  4. Gallup et al. [1999], among others, use prevalence of malaria, failing to control for endogeneity of this variable.

  5. As the correlation matrix indicates, “landlocked” is not highly correlated with any of our other geographical variables (Appendix C).

  6. See, for example, Feldmann [2003; 2005; forthcoming a], Heckman and Pagés [eds., 2004], Nickell et al. [2005], and Bassanini and Duval [2006].

  7. The tax burden on labor (“tax wedge”) would have been a preferable indicator. However, data on this indicator are available for industrial countries only. The EFW indicator “top marginal tax rate” can be regarded as a proxy for the tax burden on labor, because countries with a large (small) tax wedge usually also have a high (low) top marginal income and payroll tax rate and a low (high) income threshold at which the top marginal income tax rate applies. Besides, Feldmann [2006a] indicates that high top marginal income and payroll tax rates, and low income thresholds at which top marginal income tax rates apply, exert a detrimental impact of their own on unemployment in industrial countries.

  8. The output gap would have been the best indicator to control for the impact of business cycle fluctuations. However, data on this variable are also available for industrial countries only.

  9. These figures are based on the smallest and the largest coefficients on “very fertile soil” in the baseline regressions to explain employment and unemployment rates, respectively.

  10. Whereas “tropical area” and “frost” have a statistically significant effect on both the employment and the unemployment rate, “latitude” and “malaria ecology” each affect only one of the two dependent variables. This may be due to the fact that neither of these two independent variables is as well suited to capture the relevant geographical characteristics as “tropical area” and “frost” are (see second section).

  11. See Abrams [1999], Christopoulos and Tsionas [2002], Christopoulos et al. [2005], and Feldmann [2006a; 2007; forthcoming b].

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Authors and Affiliations

  1. Department of Economics & International Development, University of Bath, Bath, BA2 7AY, UK

    Horst Feldmann

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Appendices

Appendix A

DEFINITIONS AND SOURCES OF VARIABLES

Elevation: Mean elevation (kilometers above sea level). Source: Center for International Development [2001].

Employment rate: Percentage of working-age population in employment. Labor force survey data. Source: International Labour Office [2005].

Ethnic fractionalization: One minus the Herfindahl index of ethnic group shares, reflecting the probability that two randomly selected individuals from a population belong to different groups. The definition of ethnicity involves a combination of racial and linguistic characteristics. The classifications reflect the judgments of ethnologists and anthropologists on the appropriate definition of ethnicity. Source: Alesina et al. [2003].

Few political rights and few civil liberties: Average of Political Rights and Civil Liberties ratings from Freedom House's Freedom in the World country scores. The rating scale ranges from 1 to 7, with higher values representing less freedom. For the purpose of this paper, the ratings were divided by 10. Source: Freedom House [various issues], author's calculations.

Flexible business regulations: Subindex of the Economic Freedom of the World (EFW) index, scaled to take values between 0 and 1. Higher values indicate more flexible regulation. The subindex covers the following aspects: price controls, administrative procedures to starting a new business, time with government bureaucracy, ease of starting a new business, irregular payments. Source: Gwartney and Lawson [2005].

Flexible labor market regulations: Subindex of the Economic Freedom of the World (EFW) index, scaled to take values between 0 and 1. Higher values indicate more flexible regulation. The subindex covers the following regulations: statutory minimum wage, hiring and firing regulations, centralization of collective bargaining, unemployment benefits, military conscription. Source: Gwartney and Lawson [2005].

Frost: Share of land area with more than 5 frost-days per month in winter, after a frost-free summer. Source: Masters and McMillan [2001].

GDP growth gap: Annual growth rate of real GDP during the current year minus average annual growth rate of real GDP during the previous 10 years. Source: World Bank [2006], author's calculations.

GDP per capita: Gross domestic product per capita, converted to constant 2000 international dollars using purchasing power parity rates, divided by 1,000. Source: World Bank [2006].

Lagged GDP growth rate: Annual growth rate of real GDP, lagged by 1 year. Source: World Bank [2006].

Landlocked: Dummy variable that takes the value 1 if the country has no coastal territory on the world's oceans and seas.

Latitude: The absolute value of the latitude of the country's capital city, scaled to take values between 0 and 1. Source: La Porta et al. [1999].

Low top marginal tax rate: Subindex of the Economic Freedom of the World (EFW) index, scaled to take values between 0 and 1. Higher values indicate lower marginal income and payroll tax rates and higher income thresholds at which the top marginal income tax rates apply. Source: Gwartney and Lawson [2005].

Malaria ecology: An ecologically based variable that is predictive of malaria risk; its basic formula combines climatic factors, the presence of different mosquito vector types, and the human biting rate of the different mosquito vectors. Source: Kiszewski et al. [2004].

Mineral rich: Dummy variable that takes the value 1 if, in 1999, the country was either among the world's 15 largest miners of black coal, copper, gold, iron, lead, oil, platinum, silver, tin, or zinc, or if its share of ores and metal exports or fuel exports amounted to 25 percent or more of its merchandise exports. Source: Baratta [2002], Statistik der Steinkohlewirtschaft [2006], World Bank [2006], World Bureau of Metal Statistics [2007].

Navigable water: Share of land area within 100 km of an ocean or ocean-navigable river, excluding coastline above the winter extent of sea ice and the rivers that flow to this coastline. Source: Center for International Development [2001].

Population aged 0–14: The share of the total population that is in the age group 0–14 years. Source: World Bank [2006].

Secure property rights and strong rule of law: Subindex of the Economic Freedom of the World (EFW) index, scaled to take values between 0 and 1. Higher values indicate more secure property rights and a stronger rule of law. The subindex covers the following aspects: judicial independence, impartial courts, protection of intellectual property, military interference in rule of law and the political process, integrity of the legal system. Source: Gwartney and Lawson [2005].

Small size of government: Subindex of the Economic Freedom of the World (EFW) index, scaled to take values between 0 and 1. Higher values indicate a smaller size of the government sector. The subindex covers the following aspects: general government consumption spending as a percentage of total consumption, transfers and subsidies as a percentage of GDP, role of state-owned enterprises in the economy and government investment as a percentage of total investment, top marginal income and payroll tax rates (and income threshold at which the top marginal income tax rate applies). Source: Gwartney and Lawson [2005].

Transition country: Dummy variable for countries in transition from centrally planned to market economy.

Tropical area: Share of land area in geographical tropics. Source: Center for International Development [1999a; 2001].

Unemployment rate: Unemployed as a percentage of the labor force. Labor force survey data. Source: International Labour Office [2005].

Very fertile soil: Share of soil that is very suitable for six rainfed crops. Source: Center for International Development [1999b].

War: Dummy variable that takes the value 1 if, in the respective year, there was an interstate or internal war in the country. Source: Centre for the Study of Civil War [2005].

Appendix B

LIST OF COUNTRIES

Argentina, Australia, Austria, Bangladesh, Belgium, Bolivia, Botswana, Brazil, Bulgaria, Canada, Chile, China, Colombia, Costa Rica, Croatia, Cyprus, Czech Republic, Denmark, Dominican Republic, Ecuador, Egypt, El Salvador, Estonia, Finland, France, Germany, Greece, Guatemala, Honduras, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Latvia, Lithuania, Luxembourg, Malaysia, Mexico, Morocco, Namibia, Netherlands, New Zealand, Nicaragua, Norway, Pakistan, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Romania, Russia, Slovak Republic, Slovenia, South Africa, South Korea, Spain, Sri Lanka, Sweden, Switzerland, Taiwan, Thailand, Trinidad & Tobago, Turkey, Ukraine, United Kingdom, United States, Uruguay, Venezuela.

Appendix C

5

Table c1 Correlation matrix — geographical variables
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Feldmann, H. Geography and Labor Market Performance. Eastern Econ J 35, 190–208 (2009). https://doi.org/10.1057/eej.2008.11

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