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Oil and entrepreneurship
Energy Policy 94 (2016) 10–15
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Energy Policy journal homepage: www.elsevier.com/locate/enpol
Oil and entrepreneurship Mahdi Majbouri Babson College, Economics Division 231 Forest St., Babson Park, MA 02457, USA
H I G H L I G H T S
Profits from oil and gas have positive and negative impacts on entrepreneurship. This study explains these impacts and provides empirical evidence on them. It uses Global Entrepreneurship Monitor and WB Subsoil and Forest rents datasets. It employs a dynamic panel data estimation with country fixed effects. It shows that the negative impact dominates as corruption and oil and gas rents increase.
art ic l e i nf o
a b s t r a c t
Article history: Received 29 September 2015 Received in revised form 18 March 2016 Accepted 19 March 2016
Economic theory predicts that rents produced from natural resources, especially oil and gas, can increase opportunities for entrepreneurship, but they may also reduce engagement in entrepreneurial activities as they change incentives towards rent-seeking. Using Global Entrepreneurship Monitor (GEM) annual surveys, this study provides empirical evidence that more per capita profit from oil and gas reduces entrepreneurship only in corrupt environments. The more the corruption is, the larger is the impact. The results have important implications for policy makers, especially in resource rich developing countries. & 2016 Elsevier Ltd. All rights reserved.
JEL classification: Codes: L26 O13 Q35 Keywords: Natural resource rents Oil and gas Entrepreneurship
1. Introduction Countries whose oil, gas, or other natural resources make up a large portion of their economy are affected by both positive and negative consequences of these valuable commodities.1 One potential impact of such resources is on entrepreneurship and through two mechanisms. The first mechanism is that oil and gas rents offer new business opportunities for entrepreneurs that did not exist before through creating a new industry (oil and gas) and its supply chain, as well as increasing disposable income which leads to higher demand for products and services. Hence, they boost entrepreneurship.2 At the same time, however, a second mechanism turns on which creates disincentives for productive entrepreneurial activity. Profits from oil and gas rents reach the E-mail address: [email protected] For a review of this literature, please see van der Ploeg (2011). 2 For example, see Okkonen and Suhonen (2010) and (2013) for examples. 1
http://dx.doi.org/10.1016/j.enpol.2016.03.027 0301-4215/& 2016 Elsevier Ltd. All rights reserved.
government coffers – through taxes, or direct revenues from ownership of these resources. Potential entrepreneurs may see the opportunity to connect themselves to the government in various ways in order to exploit these oil and gas rents. In other words, profits from resource extraction in the hands of the government create incentives for potential entrepreneurs to engage in rentseeking activities and dissuade them from participating in productive entrepreneurship (Kolstad and Wiig, 2009; Tornell and Lane, 1999; Torvik, 2002; Mehlum et al., 2006; Robinson et al., 2006; Hodler, 2006). These two mechanisms have significant ramifications for the economy, especially the growth rate, entrepreneurship, and institutionalization of corruption. When profit from resource extraction becomes substantial, more people engage in rent-seeking activities rather than entrepreneurship, especially that most business opportunities have been already exploited. Therefore, the second mechanism may overcome the first one as oil and gas profits increase, especially in a corrupt environment.
M. Majbouri / Energy Policy 94 (2016) 10–15
2. The impact of oil and gas rents on entrepreneurship in theory An entrepreneur can be defined, simply, as one who is willing to take risk in order to implement a venture. Not surprisingly, Schumpeter considered an entrepreneur as a “sociologically distinct individual” (McDaniel and Bruce, 2005; Schumpeter 1934; see Thompson (2004), for supporting evidence.) Similarly, it is argued in the literature that there are traits and characteristics required in a person to make her an entrepreneur: for example, an insatiable need for achievement (Bygrave, 1989; McClelland, 1961), an internal locus of control which is the belief that the outcomes are mostly dependent upon one's own actions (Bygrave, 1989), alertness to opportunities (Kirzner, 1973, 1979), risk-taking (Bygrave, 1989; McClelland, 1961; Shane, 2004), boldness, daring, and creativity (Lumpkin and Dess, 1996; Hills et al., 1999), overconfidence (Forbes 2005; Shane, 2004), and stress tolerance (Rauch and Frese, 2007). Thompson (2004) identifies six key entrepreneurial character themes, or natural and instinctive behaviors, and argues that techniques may help people to implement ideas, “but alone they cannot compensate for missing characteristics”.3 Moreover, evidence shows inherent personal characteristics affect career choice towards self-employment (Carter et al., 2003; Lüthje and Franke, 2003). Cope (2005) argues that these are all innate abilities and permanent characteristics that evolve little over time and context. These abilities and characteristics are not found in everyone but there is a relatively fixed share of every society with these traits and characteristics who can be potential entrepreneurs. This fact is used to develop the theory in this study. Baumol (1990) argues that potential entrepreneurs can engage in two activities: (1) ‘productive entrepreneurship’: that is creating and selling products and services that are valued in the marketplace, and (2) rent-seeking or what he calls ‘unproductive entrepreneurship’: that is creating connections with sources of rent, and competing to capture more of the rent in the economy.4 ‘Productive entrepreneurship’ is the growth enhancing form of entrepreneurship. It is what widely referred to as entrepreneurship, although rent seeking is also an activity potential entrepreneurs can engage in. Rent seeking is possible when there are
B
C
A
rents
Rents per Rent-seeker
rents’ rents’’
Profits per Entrepreneur
Using a unique dataset on entrepreneurship, which covers 80 countries around the world and over time, this study offers the first empirical evidence verifying this non-linear relationship between oil and gas profits, and entrepreneurship. Using ArellanoBond estimator to correct for endogeneity from lagged values of entrepreneurship and country fixed effects (Arellano and Bond, 1991), and controlling for lagged values of per capita GDP, a very important predictor of entrepreneurial activity across countries, this paper shows that as profit from oil and gas increases, productive entrepreneurship decreases, since rent seeking activities overcome benefits of these profits. It also shows that the reduction in entrepreneurship only exists in corrupt environments and more corruption exacerbates the negative impact of oil and gas profits. The rest of this paper is constructed as follows: Section 2 discusses the theory that relates oil rents to entrepreneurship. In Section 3, the datasets used in this paper are explained. Section 4 provides the estimation strategy and the results. Section 5 is the conclusion which discusses implications for policy and research.
11
profits’
profits
Productive Entrepreneurs
Rent-seekers
Fig. 1. Productive Entrepreneurship and Rent-Seeking. Note: The profits curve shows that the larger are the profits, more people engage in productive activities. On the other hand, the total rent in the economy is fixed. The rents curves show that as more people engage in rent-seeking, each will end up with a smaller share. The equilibrium happens when the average profits are the same as the average rent, i.e. where the two lines cross. As rents increase, the rents curve shifts to the left and with it the equilibrium. Hence, it decreases the number of productive entrepreneurs. van der Ploeg (2011), based on Mehlum et al. (2006).
rents available in the economy and particularly when rents are concentrated in a few sources that are prone to corruption, like the government (for example, when government enjoys sizable profits from owning or taxing natural resources.). The potential entrepreneurs choose between these two activities (entrepreneurship and rent seeking) based on the structure of returns from them.5 Fig. 1 shows the two entrepreneurial activities graphically. The horizontal axis represents the number of potential entrepreneurs. They can participate in productive or rent-seeking activities. As more of them choose productive activity, fewer will be rent-seekers. The vertical axis on the left shows profits per entrepreneur. The number of potential entrepreneurs who choose productive activity depends on the profits earned from it. The larger are the profits per entrepreneur, the more people will engage in productive activities. It is the simple law of supply and is clear from the profits lines that are upward-sloping. On the other hand, the total rent in the economy is fixed. So if more people engage in rent-seeking, each ends up with a smaller share (i.e. smaller rent). The rents curves demonstrate such phenomenon. The vertical axis on the right denotes rent per rentseeker. The more people become rent-seekers, the smaller will be the average rent that each receives (rent per rent-seeker). The potential entrepreneur chooses productive activities if the average profits (profits per entrepreneur) is larger than the average rents. Therefore, the equilibrium number of entrepreneurs and rentseekers happens when the average profits are the same as the average rent. This is where no one wants to switch from being a productive entrepreneur to a rent-seeker and vice versa. When there is no natural resource in the economy, there is still opportunity for rent grabbing for example via legal loopholes, or connections with the government. In this situation, the rent curve showing rent per rent-seeker is represented by the rents curve in Fig. 1 and the supply curve for the entrepreneurs is depicted by the profits curve. The equilibrium, when no natural resource is in the economy, is point A on the graph. As soon as a valuable natural resource is discovered, it provides many new opportunities for entrepreneurs, since it leads to creation of a new industry (resource extraction) with all its supply chain. This leads to a substantial hike in expected profits for
3
For more studies, see Puga and Garcia (2012). Baumol (1990) also discusses ‘destructive entrepreneurship’. In this form of entrepreneurship, the entrepreneur takes advantage of opportunities to engage in pillaging, confiscation, and other expropriation activities that are destructive to the economy but profitable to the entrepreneur. 4
5 Of course, some entrepreneurs engage in a mix of productive and rentseeking endeavors. But, this does not affect the spirit and result of the theory that follows.
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M. Majbouri / Energy Policy 94 (2016) 10–15
entrepreneurs who enter this industry. Therefore, the introduction of the natural resource to the economy is revolutionary and shifts the expected profits curve substantially to profits'. At the same time, more income in the hands of the government (through owning or taxing the resource) increases the total rent in the economy. So the rents curve shifts to rent’' especially when rents are concentrated in the hands of corrupt governments and bureaucracies. Therefore, the equilibrium moves from A to B which means the number of productive entrepreneurs decreases and the number of rent-seekers increases. When corruption is minimal, more oil and gas profits in the economy does not automatically translate into more rents. Corruption control mechanisms limit the amount of rent-seeking in the economy. In this situation, the rents curve may not increase as much. In Fig. 1, rent may only shift to rent'. Profits curve, however, shift at least as much as before to profits'. These shifts in rents and profits curve move equilibrium to point C. Therefore, productive entrepreneurship increases or stays the same (relative to point A.) It can be argued that shift in the profits curve is probably larger than profits' in an environment with less corruption, but this does not affect the argument above.6 In summary, profits from extraction of natural resources, and particularly oil and gas, should have a negative impact on entrepreneurship in corrupt environments and a positive or at least zero impact on entrepreneurship when corruption is minimal. Using data on productive entrepreneurship and oil and gas annual profits across countries and over time, this study provides empirical evidence for this relationship. The data, estimation strategy and results are discussed in the following sections.
3. Data This study uses four data sets. The first is the Global Entrepreneurship Monitor (GEM) surveys which cover about 80 countries and extend over ten years. GEM is the largest study of entrepreneurial dynamics in the world and its main purpose is to measure productive entrepreneurial activity and understand entrepreneurial behavior, attitudes, and aspirations around the world.7 The project started in 1999 with 10 countries and grew to about 70 countries in 2012. Since 2004, the quality of the data, collected in various countries, has been professionally controlled by a team of experts, making it very reliable. Because of this, this study only uses the surveys after 2004. But because the oil and gas rents data are available until 2008 only, this research would not be able to use the surveys after 2008. Hence, only surveys between 2004 and 2008 could be exploited for this study. GEM consists of 6 The evidence also shows that rise in oil and gas profits has an adverse effect on institutional quality when there is little history of good institutions. Using a panel dataset covering ninety-nine countries during 1980–2004 and controlling for income, time-varying common shocks, regional fixed-effects, and some other covariates, Bhattacharyya and Hodler (2010) find that natural resources only induce corruption in countries that have endured a nondemocratic regime for more than 60% of the years since 1956. Vicente (2010) compares changes in perceived corruption in the island Sao Tome and the island of Cape Verde which have similar histories, culture, and political institutions after a natural experiment – a significant oil discovery in the island of Sao Tome. He finds that corruption increased by close to 10% after the announcements of a significant oil discovery in 1997–99. In a quasiexperimental setting and using data on Brazilian municipalities, Fernanda Brollo et al. (2013) show that an increase in oil profits of 10% for a municipality raises corruption by 17–24%, and increases the likelihood of the incumbent remaining to office by 7%. It also shrinks the fraction of its opponents holding a college degree by 7%. All these mean that in countries with little history of good institutions an increase in oil and gas profits deteriorates the institutional quality and shifts the rents curve more towards left. 7 More information about the GEM project may be found at www.gemconsor tium.org.
two surveys: the Adult Population Survey (APS) and the National Expert Survey (NES).8 APS is a harmonized, nationally representative random population survey gathered annually from individuals in each participating country. Within country sample size ranges from 2000 to 45,000. In each country, a team is responsible for conducting the survey. A local survey firm is carefully chosen to collect data for a standard survey questionnaire. Survey questions are standard globally and conducted simultaneously across all countries between May and August of every year. Surveys are collected via phone and where phone penetration is low by door-to-door interviews. A standard protocol governs sampling, coding, weighting and other data collection procedures. A central coordination team of experts monitors the sampling procedure in each country and the accuracy and compatibility of data across countries. It requests for clarifications and corrections for coding and weightings, whenever necessary, so that the protocol would be followed by all national teams. At the end of collection procedure, the central coordination team harmonizes the data across countries, and offers them to public on the GEM consortium website.9 This study uses APS series to measure productive entrepreneurial activity for several reasons. First, APS is a population survey and asks individuals whether they engage in businesses. If the individual owns or manages a business, or is in the process of starting one, she will be asked follow-up questions about the business and herself. Therefore, it covers microenterprises which are notoriously difficult to account for in firm surveys. Second, APS accounts for informal businesses which are usually neglected in firm surveys, since firm surveys create their sample based on registered businesses. Third, APS datasets are collected according to a standard protocol across countries and are quality-controlled and harmonized by a central team. Therefore, entrepreneurial activities are measured consistently and easily comparable across countries. This is very important in cross-country comparison and is rarely the case. For example, unlike APS datasets, some economic indicators are measured differently in each country which renders them incomparable. Fourth, APS data account for those who failed as well. Failure is an important part of entrepreneurship which is usually not measured in other surveys. All these reasons make GEM surveys the best for studying entrepreneurship across countries. Data on oil and gas rents come from World Bank Subsoil and Forest Rents dataset. It has annual rents, i.e. profits, from oil and gas for every country from 1970 to 2008. These rents are divided by population to obtain rents per capita which is the most reliable measure of the significance of natural resource in an economy (For a discussion, please see Ross (2008)). Population data and GDP per capita in 2005 constant prices are from World Bank Development Indicators. Corruption Perceptions Index, which is used as a measure of corruption, is obtained from Transparency International. This study employs countries which produce oil or gas (even in small volumes) even if they are net-importers. The sample has 50 countries. Table 1 contains the summary statistics of all the variables used for this sample. GDP and oil and gas rents per capita are deflated to account for inflation. 8 NES is an expert opinion survey containing opinions about nine dimensions of entrepreneurial environment in each country. These dimensions are finance, government policies and programs, entrepreneurial education and training, R&D transfer, commercial and professional infrastructure, entry regulation, physical infrastructure and services, and cultural and social norms. This study does not employ NES surveys and only uses APS data. 9 www.gemconsortium.org; Details about the procedures used to collect and harmonize GEM data can be found in Reynolds et al. (2005). An overview is in Minniti (2011).
M. Majbouri / Energy Policy 94 (2016) 10–15 Table 1 – Summary statistics.
13
Table 2 – Entrepreneurial Activity and Resource Rents; Arellano Bond Estimations with Country Fixed Effects. Mean
Std. dev.
Min
Max
0.2 21.5 6.6 3.4 9.9 0.5 43.1
0.1 3.1 2.1 2.1 1.0 0.5 15.2
0.05 13.1 2.2 0.4 6.7 0.0 9.0
0.66 26.8 9.6 7.8 11.1 1.0 104.0
All Productive entrepreneurship rate ln(Rents per capita) Transparency International CPI Corruption index ln(GDP per capita) Female' Age
Note: Productive entrepreneurship rate shows the share of individuals in the population of the country that are productive entrepreneurs. An individual is considered a productive entrepreneur if at the time of the survey, she was engaged in starting a business, or a new venture in an existing business, or owned an established business, or had shut down a business in the 12 months prior to the survey. ln (Rents per capita) represents annual profits from oil and gas rents deflated for inflation. Transparency International CPI is the Corruption Perceptions index which is between zero (fully corrupt) and ten (no corruption). Corruption is equal to ten minus Transparency International CPI. ln (GDP per capita) and its squared are in 2005 constant prices for each country and over time. Female is a dummy equal to one if the individual is female and zero otherwise. Age is measured in years. Number of countries: 50 countries Years: 2004 through 2008.
(1)
The rest of this paper demonstrates if rents have any impact on entrepreneurial activity. Consider the following dynamic panel data model:
Hkt =αHkt −1+β ln (Rentkt ) + γ ′Zkt +ck+ + εkt
(1)
(3)
(4)
L. entrepreneurship
0.004
0.154
0.165
0.009
ln (Rentspercapita)
(0.354) 0.037nn
(0.337) 0.044nn
(0.334) 0.039
(0.304) 0.036
(0.017)
(0.017)
(0.039) 0.021n
(0.034) 0.022nn
(0.012) 0.361
(0.010) 0.094
×Corruption L. ln (GDP per capita)
(L. ln (GDP per capita))2
1.172
0.959
(1.483) 0.078
(1.246) 0.066
(1.303) 0.039
(0.981) 0.024
(0.077)
(0.066) 0.111 (0.124) 0.017 (0.015) 0.017
(0.067)
(0.052) 0.125 (0.109) 0.018 (0.014) 0.018
Female Age Age2 ×10−2
(0.014) Observations Number of countries
4. Estimation and results
(2)
58 27
58 27
(0.013) 58 27
58 27
Note: The dependent variable is a dummy equal to one if the individual is a productive entrepreneur in the past year (description in the text and notes for Table 1). L. is the lag operator. For description and summary statistics of variable, please see Table 1. 50 countries and 5 years (2004 through 2008) are in the sample. Not all countries have data for all years. Therefore, the number of countries with at least three observations required for Arellono-Bond estimation is 27. Robust-heteroskedastic standard errors are in parentheses nn
in which, Hkt is the share of entrepreneurs out of the adult population in country k in year t and Hkt − 1 is its lagged value. ln (Rentkt ), and Zkt are respectively natural log of oil and gas rents per capita, and observed characteristics of country k in year t . f (Rentkt ) is a function of Rentkt . ck is the country k fixed effect which controls for all characteristics of country k that are fixed over time. These include but not limited to culture, history, traditions, social norms, political, social and economic institutions, laws and regulations, and time-constant demographic characteristics. εkt are independently distributed disturbances. Table 2 presents the results for the least squares estimations of Eq. (1), when the dependent variable is the share of population who was a productive entrepreneur in country k and year t . In this study, a productive entrepreneur is defined as someone for whom any of the following four statements in the GEM surveys is true:
n
po 0.10. p o 0.05.
As entrepreneurship rate in a country may have a dynamic relationship with its lagged value over time, Hkt − 1 is included in Eq. (1). But including the lagged value of the dependent variable with fixed effects creates endogeneity (Nickell, 1981). The bias from this endogeneity has an inverse relationship with the number of time periods. Since there are only five years of data, the bias can be substantial. Therefore, Arellano-Bond estimator is used to instrument for lagged values of the dependent variable and consistently estimate the regression (Arellano and Bond, 1991). Like GDP per capita, oil and gas rents per capita has a large variation across countries. Hence, similar to GDP per capita, one can use natural log of oil and gas rents per capita. As Fig. 2 shows,
You are, alone or with others, currently trying to start a new
business, including any self-employment or selling any goods or services to others. You are, alone or with others, currently trying to start a new business or a new venture for your employer – an effort that is part of your normal work. You are, alone or with others, currently the owner of a company you help manage, self-employed, or selling any goods or services to others. You have, in the past 12 months, sold, shut down, discontinued or quit a business you owned and managed, any form of selfemployed, or selling goods or services to anyone.
The fourth statement is particularly necessary to be included as failure is an important part of entrepreneurship. One of the strengths of GEM surveys is that they account for those who failed as well. Note that GEM, like any other survey of entrepreneurship, only measures productive entrepreneurship which is all we need for this study. From now on, we refer to productive entrepreneurship when we mention entrepreneurship.
0.25
0.2
0.15
0.1
0.05
0
0
10 20 ln(Real rents per capita + 1)
30
Fig. 2. Distribution of natural log of oil and gas rents per capita. Note: real rents per capita is the total profits (price minus the cost of production) of oil and gas in constant prices deflated and divided by population of the country.
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M. Majbouri / Energy Policy 94 (2016) 10–15
the distribution of this variable is discontinuous between 0 and 13. About twenty percent of the observations have the value of zero and the rest are above 13. Only countries with non-zero oil and gas rent are used in the sample. Table 2 reports the regressions based on Eq. (1) for the whole sample. The first column has lagged values of the dependent variable, L. entrepreneurship, log of rents per capita, and country fixed effects. It also contains lagged values of log of GDP per capita and its squared, important predictors of entrepreneurship rate in a country. Lagged values of GDP per capita are used since current values could create simultaneity. Consistent with the theory discussed in Section 2, the coefficient of log of rents per capita is negative. The size of the coefficient implies that doubling oil and gas rents reduces productive entrepreneurship rate by about 4 percentage points. In the second column, some country characteristics like the average age of the population and its squared as well as sex ratio of the population (i.e. female) are included. Age and gender are strongly correlated with the probability of individuals engaging in entrepreneurial activity. The negative coefficient of rents remains robust both in statistical significance and size. These results are robust to many omitted variables. Lagged value of the dependent variable, L. entrepreneurship, controls for any dynamic relationship in entrepreneurship over time. Interestingly, the coefficient of this lagged variable is insignificant in all columns, suggesting that there is no dynamic relationship in these regressions. The country fixed effects control for any feature of a country that is constant over time. Therefore, all time-constant factors including but not limited to history, culture, religion, social norms, time-constant traits and attitudes, political and economic institutions, time-constant laws and regulations, do not bias the results. There might still be country-specific time-varying factors that would be correlated with GDP and rents per capita as well as entrepreneurial activity, and hence, bias the results. It is not possible to control for such factors with country-time fixed effects as rents vary across country and time. Based on the theory explained in Section 2, one may argue that the impact of oil and gas rents should be larger in countries that are more corrupt. In order to test this conjecture, one can interact oil and gas rents with a measure of corruption in the country. Transparency International measures corruption globally every year and reports it in an index called Corruption Perceptions Index which is between 0 (the most corrupt) and 10 (the least corrupt). In other words, the larger is this measure, the less the country is corrupt. In order to get a measure that is increasing in corruption, one can subtract Corruption Perception Index from 10. This way the least corrupt environment gets a zero grade and the most corrupt one is marked 10. This new variable, entitled Corruption, is included in the regressions to simplify the interpretation of the results. Columns (3) and (4) of Table 2 report these results using the sample of oil or gas producers. We observe that the negative impact of oil and gas rent only exists when there is corruption and as corruption increases, productive entrepreneurship is discouraged more. Interestingly, the impact of oil and gas rents when corruption does not exist is positive but statistically insignificant. In other words, profits from oil and gas has positive or no impact on productive entrepreneurship in countries such as United Kingdom, Canada, and Norway, which have very low corruption. The turning point is roughly at corruption index of 2.
5. Conclusion and policy implications This study offered the first empirical evidence for the inverse relationship between the size of oil and gas rents and productive entrepreneurship. This relationship is only pronounced in a
corrupt environment. Profits from oil and gas boost productive entrepreneurship, especially in a less corrupt environment, as they offer new opportunities through creating a new industry (oil and gas), as well as increasing disposable incomes and demand for new products and services. But when corruption exists, more income for the governments, through owning or taxing oil and gas resources, creates opportunities for rent-seeking. This entices potential entrepreneurs to choose rent-seeking rather than productive entrepreneurship because it is more lucrative. Therefore, productive entrepreneurship declines. One important lesson for policy is that in developing countries, where corruption is prevalent, oil and gas rent may not be advantageous for the economy and specifically productive entrepreneurship. It creates new sources of rents, thereby increasing the expected returns to rent-seeking activities. One solution is to reduce the amount of rent that is available to the government. Ideas such as transparent commodity funds, and lump-sum distributions are helpful in reducing rent-seeking. Governments can create transparent sovereign wealth funds to save some of the oil and gas profits especially when those profits are rising and new rent-seeking opportunities are created. Since these savings take excess profits out of the economy and into the transparent fund, fewer new opportunities for rent-seeking will be created when the oil and gas profits increase. Another way to reduce rent-seeking activities is to distribute all excess profits from oil and gas among the general public. This is the idea based on Alaska Permanent Fund which by law distributes half of investment earnings, equally among the population. As a result, less rent becomes available for rent-seekers.10 Another important lesson is that fighting corruption and creating more transparency is the key in harnessing natural resources. Since these profits can become a source of corruption and bad institutions themselves,11 it is difficult to mix oil and gas with transparency but the resulting potion is the elixir of fast and continuous growth. One solution is that the whole process of extraction, transportation, refinement, and revenue management of oil and gas is audited by international auditors. Joining the Extractive Industries Transparency Initiative (EITI) provides a standard framework for governments, and the industry alike, on how to reduce corruption. Grass-roots pressure in the developed countries have pushed the international corporations to sign off on social responsibility schemes such as EITI by which they have to follow stricter rules in dealing with resource-rich governments. Under the EITI initiative, the oil companies need to publish what they pay to governments and the governments need to show their receipts. The initiative matches these two figures and publishes the result for the general public. Wenar (2008) argues that governments in very corrupt but resource rich countries that are appropriating oil and gas revenues are in fact stealing it from their citizens. Therefore, the multinational corporations who are involved in the process of discovery, extraction, transportation, and refinement with these governments can be held accountable for dealing with them and legal action should be pursued against them where there is strong rule of law (such as The United States or Europe). This discourages these multinational corporations from doing business with the corrupt governments and encourages the states to enact reforms and pursue institutional change. The problem with this approach, 10 Sala-i-Martin and Subramanian (2013) and Birdsall and Subramanian (2004) suggest this idea for Iraq and Nigeria. El-Anshasy et al. (2015) offer detailed policy suggestions in this arena. Majbouri (2015) calculated the opportunity cost of not following the Hartwik rule (as the best policy) for the economies of oil producing countries in the Middle East and North Africa region. 11 See Bhattacharyya and Hodler (2010) for panel data evidence, Vicente (2010) and Borello et al. (2010) for quasi-experimental evidence.
M. Majbouri / Energy Policy 94 (2016) 10–15
he acknowledges, is that corporations that operate outside jurisdictions with strong rule of low, such as Chinese corporations, are immune to these legal actions. Wenar, however, proposes “anti-theft tariffs”, on for instance Chinese exports to Western countries, equal to the size of business with those corrupt governments. The collected tariffs will later be transferred to the citizens of those countries as soon as minimum standards of institutional reforms are in place. This solution, however, may trigger a global tariff war and the result is not beneficial for anyone. Another solution is to establish an international organization like WTO (or its predecessor GATT) that oversees and governs involvements of all internationally active corporations in extractive industries. This organization should be formed through multilateral negotiations between governments of all countries that have extractive industries which operate globally. The goal will be to form multilateral agreements on the structure and mechanism of disputes and punishments for breaching ethical rules of doing business with corrupt governments of resource-rich countries. This international institution can be part of existing institutions such as WTO. The agreements should be comprehensive and need to be ratified by all parties. Like climate change and environmental degradation, this is an issue that needs global initiative and commitment. The punishment may not turn out to be as severe as one would hope for but this new institution will provide more transparency in the process and clearly depicts to citizens of those countries how their governments and international corporations use revenues from their natural resources. More research and innovative ideas are required to solve this global problem. In addition to these issues, one interesting fact to note is that some government policies that try to encourage entrepreneurship, are themselves becoming a source of rent-seeking activity. For instance, governments sometimes sponsor entrepreneurs, subsidize their cost of capital, labor, or reduce their taxes. There are also many government sponsored competitions that choose entrepreneurs and give them awards or special treatments. But, these policies usually become a source of rent for rent-seekers themselves, and lead to worse outcomes. The issues of adverse selection and moral hazard are prevalent in these cases. Many potential entrepreneurs write proposals or define projects just to acquire these rents from the government. It is always difficult for governments to choose the winners, the right entrepreneurs and the right projects. In many cases, projects that are not feasible or economical but attractive and extravagant have a higher chance of being chosen (adverse selection). This results in many bad apples wasting resources. In addition, entrepreneurs who enjoy these benefits have less incentive to work as hard and attain success (moral hazard). More research on understanding the interrelation of oil and gas and corruption is necessary and more ideas to encourage entrepreneurship that are feasible in developing countries are required.
Acknowledgements I am sincerely grateful to the editor and the reviewer of Energy Policy for the thoughtful comments and helpful suggestions. My thanks also goes to Babson Faculty Research Fund (BFRF) for the financial support of this research and to Candida Brush, Donna J. Kelley, Maria Minniti, and BFRF reviewers for their comments. All the remaining errors are mine.
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Dealing with the challenges in resourcerich Arab economies: policy proposals and political economy considerations, Working Paper. Forbes, D.P., 2005. Are Some Entrepreneurs More Overconfident Than Others? J. Bus. Ventur. 20 (5), 623–640. Hills, G.E., Shrader, R.C., Lumpkin, G.T., 1999. Opportunity recognition as a creative process. In: Frontiers of Entrepreneurship Research, Babson College, Wellesley, MA, pp. 216–227. Hodler, R., 2006. The Curse of Natural Resources in Fractionalized Countries. Eur. Econ. Rev. 50 (6), 1367–1386. Kirzner, I.M., 1973. Competition and Entrepreneurship. University of Chicago Press, Chicago. Kirzner, I.M., 1979. Perception, Opportunity, and Profit: Studies in the Theory of Entrepreneurship. University of Chicago Press, Chicago. Kolstad, Ivar, Wiig, Arne, 2009. It is the rents, stupid! the political economy of the resource curse. Energy Policy 37 (12), 5317–5325. Lumpkin, G.T., Dess, G.G., 1996. Clarifying the entrepreneurial orientation construct and linking it to performance. Acad. Manag. Rev. 21 (1), 135–172. Lüthje, C., Franke, N., 2003. The ‘making’ of an entrepreneur: testing a model of entrepreneurial intent among engineering students at MIT. RD Manag. 33 (2), 135–147. Majbouri, M., 2015. Calculating the income counterfactuals for oil producing countries of the MENA region. Resour. Policy 44, 47–56. Minniti, Maria, 2011. Data appendix. In: Minniti, Maria (Ed.), The Dynamics of Entrepreneurship: Evidence from Global Entrepreneurship Monitor Data. Oxford University Press, Oxford, pp. 307–312. McClelland, D.C., 1961. The Achieving Society. Van Nostrand Reinhold, Princeton. McDaniel, Bruce A., 2005. A contemporary view of Joseph A. Schumpeter's theory of the entrepreneur. J. Econ. Issues 39 (2), 485–489. Mehlum, Halvor, Moene, Karl, Torvik, Ragnar, 2006. Institutions and the resource curse. Econ. J. 116 (508), 1–20. Nickell, Stephen, 1981. Biases in dynamic models with fixed effects. Econometrica 49 (6), 1417–1426. Okkonen, Lasse, Suhonen, Niko, 2010. Business models of heat entrepreneurship in Finland. Energy Policy 38 (7), 3443–3452. Okkonen, Lasse, Suhonen, Niko, 2013. The Energy Services Company (ESCo) as business model for heat entrepreneurship: a case study of North Karelia, Finland. Energy Policy 61, 783–787. López Puga, Jorge, García García, Juan, 2012. A comparative study on entrepreneurial attitudes modeled with logistic regression and bayes nets. Span. J. Psychol. 15, 03. Rauch, A., Frese, M., 2007. Let's put the person back into entrepreneurship research: a meta-analysis on the relationship between business owners’ personality traits, business creation, and success. Eur. J. Work Organ. Psychol. 16 (4), 353–385. Reynolds, P.N., Bosma, N., Autio, E., Hunt, S., De Bono, M., Servais, I., Lopez-Garcia, P., Chin, N., 2005. Global entrepreneurship monitor: data collection design and implementation, 1998–2003,. 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Contents lists available at ScienceDirect
Energy Policy journal homepage: www.elsevier.com/locate/enpol
Oil and entrepreneurship Mahdi Majbouri Babson College, Economics Division 231 Forest St., Babson Park, MA 02457, USA
H I G H L I G H T S
Profits from oil and gas have positive and negative impacts on entrepreneurship. This study explains these impacts and provides empirical evidence on them. It uses Global Entrepreneurship Monitor and WB Subsoil and Forest rents datasets. It employs a dynamic panel data estimation with country fixed effects. It shows that the negative impact dominates as corruption and oil and gas rents increase.
art ic l e i nf o
a b s t r a c t
Article history: Received 29 September 2015 Received in revised form 18 March 2016 Accepted 19 March 2016
Economic theory predicts that rents produced from natural resources, especially oil and gas, can increase opportunities for entrepreneurship, but they may also reduce engagement in entrepreneurial activities as they change incentives towards rent-seeking. Using Global Entrepreneurship Monitor (GEM) annual surveys, this study provides empirical evidence that more per capita profit from oil and gas reduces entrepreneurship only in corrupt environments. The more the corruption is, the larger is the impact. The results have important implications for policy makers, especially in resource rich developing countries. & 2016 Elsevier Ltd. All rights reserved.
JEL classification: Codes: L26 O13 Q35 Keywords: Natural resource rents Oil and gas Entrepreneurship
1. Introduction Countries whose oil, gas, or other natural resources make up a large portion of their economy are affected by both positive and negative consequences of these valuable commodities.1 One potential impact of such resources is on entrepreneurship and through two mechanisms. The first mechanism is that oil and gas rents offer new business opportunities for entrepreneurs that did not exist before through creating a new industry (oil and gas) and its supply chain, as well as increasing disposable income which leads to higher demand for products and services. Hence, they boost entrepreneurship.2 At the same time, however, a second mechanism turns on which creates disincentives for productive entrepreneurial activity. Profits from oil and gas rents reach the E-mail address: [email protected] For a review of this literature, please see van der Ploeg (2011). 2 For example, see Okkonen and Suhonen (2010) and (2013) for examples. 1
http://dx.doi.org/10.1016/j.enpol.2016.03.027 0301-4215/& 2016 Elsevier Ltd. All rights reserved.
government coffers – through taxes, or direct revenues from ownership of these resources. Potential entrepreneurs may see the opportunity to connect themselves to the government in various ways in order to exploit these oil and gas rents. In other words, profits from resource extraction in the hands of the government create incentives for potential entrepreneurs to engage in rentseeking activities and dissuade them from participating in productive entrepreneurship (Kolstad and Wiig, 2009; Tornell and Lane, 1999; Torvik, 2002; Mehlum et al., 2006; Robinson et al., 2006; Hodler, 2006). These two mechanisms have significant ramifications for the economy, especially the growth rate, entrepreneurship, and institutionalization of corruption. When profit from resource extraction becomes substantial, more people engage in rent-seeking activities rather than entrepreneurship, especially that most business opportunities have been already exploited. Therefore, the second mechanism may overcome the first one as oil and gas profits increase, especially in a corrupt environment.
M. Majbouri / Energy Policy 94 (2016) 10–15
2. The impact of oil and gas rents on entrepreneurship in theory An entrepreneur can be defined, simply, as one who is willing to take risk in order to implement a venture. Not surprisingly, Schumpeter considered an entrepreneur as a “sociologically distinct individual” (McDaniel and Bruce, 2005; Schumpeter 1934; see Thompson (2004), for supporting evidence.) Similarly, it is argued in the literature that there are traits and characteristics required in a person to make her an entrepreneur: for example, an insatiable need for achievement (Bygrave, 1989; McClelland, 1961), an internal locus of control which is the belief that the outcomes are mostly dependent upon one's own actions (Bygrave, 1989), alertness to opportunities (Kirzner, 1973, 1979), risk-taking (Bygrave, 1989; McClelland, 1961; Shane, 2004), boldness, daring, and creativity (Lumpkin and Dess, 1996; Hills et al., 1999), overconfidence (Forbes 2005; Shane, 2004), and stress tolerance (Rauch and Frese, 2007). Thompson (2004) identifies six key entrepreneurial character themes, or natural and instinctive behaviors, and argues that techniques may help people to implement ideas, “but alone they cannot compensate for missing characteristics”.3 Moreover, evidence shows inherent personal characteristics affect career choice towards self-employment (Carter et al., 2003; Lüthje and Franke, 2003). Cope (2005) argues that these are all innate abilities and permanent characteristics that evolve little over time and context. These abilities and characteristics are not found in everyone but there is a relatively fixed share of every society with these traits and characteristics who can be potential entrepreneurs. This fact is used to develop the theory in this study. Baumol (1990) argues that potential entrepreneurs can engage in two activities: (1) ‘productive entrepreneurship’: that is creating and selling products and services that are valued in the marketplace, and (2) rent-seeking or what he calls ‘unproductive entrepreneurship’: that is creating connections with sources of rent, and competing to capture more of the rent in the economy.4 ‘Productive entrepreneurship’ is the growth enhancing form of entrepreneurship. It is what widely referred to as entrepreneurship, although rent seeking is also an activity potential entrepreneurs can engage in. Rent seeking is possible when there are
B
C
A
rents
Rents per Rent-seeker
rents’ rents’’
Profits per Entrepreneur
Using a unique dataset on entrepreneurship, which covers 80 countries around the world and over time, this study offers the first empirical evidence verifying this non-linear relationship between oil and gas profits, and entrepreneurship. Using ArellanoBond estimator to correct for endogeneity from lagged values of entrepreneurship and country fixed effects (Arellano and Bond, 1991), and controlling for lagged values of per capita GDP, a very important predictor of entrepreneurial activity across countries, this paper shows that as profit from oil and gas increases, productive entrepreneurship decreases, since rent seeking activities overcome benefits of these profits. It also shows that the reduction in entrepreneurship only exists in corrupt environments and more corruption exacerbates the negative impact of oil and gas profits. The rest of this paper is constructed as follows: Section 2 discusses the theory that relates oil rents to entrepreneurship. In Section 3, the datasets used in this paper are explained. Section 4 provides the estimation strategy and the results. Section 5 is the conclusion which discusses implications for policy and research.
11
profits’
profits
Productive Entrepreneurs
Rent-seekers
Fig. 1. Productive Entrepreneurship and Rent-Seeking. Note: The profits curve shows that the larger are the profits, more people engage in productive activities. On the other hand, the total rent in the economy is fixed. The rents curves show that as more people engage in rent-seeking, each will end up with a smaller share. The equilibrium happens when the average profits are the same as the average rent, i.e. where the two lines cross. As rents increase, the rents curve shifts to the left and with it the equilibrium. Hence, it decreases the number of productive entrepreneurs. van der Ploeg (2011), based on Mehlum et al. (2006).
rents available in the economy and particularly when rents are concentrated in a few sources that are prone to corruption, like the government (for example, when government enjoys sizable profits from owning or taxing natural resources.). The potential entrepreneurs choose between these two activities (entrepreneurship and rent seeking) based on the structure of returns from them.5 Fig. 1 shows the two entrepreneurial activities graphically. The horizontal axis represents the number of potential entrepreneurs. They can participate in productive or rent-seeking activities. As more of them choose productive activity, fewer will be rent-seekers. The vertical axis on the left shows profits per entrepreneur. The number of potential entrepreneurs who choose productive activity depends on the profits earned from it. The larger are the profits per entrepreneur, the more people will engage in productive activities. It is the simple law of supply and is clear from the profits lines that are upward-sloping. On the other hand, the total rent in the economy is fixed. So if more people engage in rent-seeking, each ends up with a smaller share (i.e. smaller rent). The rents curves demonstrate such phenomenon. The vertical axis on the right denotes rent per rentseeker. The more people become rent-seekers, the smaller will be the average rent that each receives (rent per rent-seeker). The potential entrepreneur chooses productive activities if the average profits (profits per entrepreneur) is larger than the average rents. Therefore, the equilibrium number of entrepreneurs and rentseekers happens when the average profits are the same as the average rent. This is where no one wants to switch from being a productive entrepreneur to a rent-seeker and vice versa. When there is no natural resource in the economy, there is still opportunity for rent grabbing for example via legal loopholes, or connections with the government. In this situation, the rent curve showing rent per rent-seeker is represented by the rents curve in Fig. 1 and the supply curve for the entrepreneurs is depicted by the profits curve. The equilibrium, when no natural resource is in the economy, is point A on the graph. As soon as a valuable natural resource is discovered, it provides many new opportunities for entrepreneurs, since it leads to creation of a new industry (resource extraction) with all its supply chain. This leads to a substantial hike in expected profits for
3
For more studies, see Puga and Garcia (2012). Baumol (1990) also discusses ‘destructive entrepreneurship’. In this form of entrepreneurship, the entrepreneur takes advantage of opportunities to engage in pillaging, confiscation, and other expropriation activities that are destructive to the economy but profitable to the entrepreneur. 4
5 Of course, some entrepreneurs engage in a mix of productive and rentseeking endeavors. But, this does not affect the spirit and result of the theory that follows.
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M. Majbouri / Energy Policy 94 (2016) 10–15
entrepreneurs who enter this industry. Therefore, the introduction of the natural resource to the economy is revolutionary and shifts the expected profits curve substantially to profits'. At the same time, more income in the hands of the government (through owning or taxing the resource) increases the total rent in the economy. So the rents curve shifts to rent’' especially when rents are concentrated in the hands of corrupt governments and bureaucracies. Therefore, the equilibrium moves from A to B which means the number of productive entrepreneurs decreases and the number of rent-seekers increases. When corruption is minimal, more oil and gas profits in the economy does not automatically translate into more rents. Corruption control mechanisms limit the amount of rent-seeking in the economy. In this situation, the rents curve may not increase as much. In Fig. 1, rent may only shift to rent'. Profits curve, however, shift at least as much as before to profits'. These shifts in rents and profits curve move equilibrium to point C. Therefore, productive entrepreneurship increases or stays the same (relative to point A.) It can be argued that shift in the profits curve is probably larger than profits' in an environment with less corruption, but this does not affect the argument above.6 In summary, profits from extraction of natural resources, and particularly oil and gas, should have a negative impact on entrepreneurship in corrupt environments and a positive or at least zero impact on entrepreneurship when corruption is minimal. Using data on productive entrepreneurship and oil and gas annual profits across countries and over time, this study provides empirical evidence for this relationship. The data, estimation strategy and results are discussed in the following sections.
3. Data This study uses four data sets. The first is the Global Entrepreneurship Monitor (GEM) surveys which cover about 80 countries and extend over ten years. GEM is the largest study of entrepreneurial dynamics in the world and its main purpose is to measure productive entrepreneurial activity and understand entrepreneurial behavior, attitudes, and aspirations around the world.7 The project started in 1999 with 10 countries and grew to about 70 countries in 2012. Since 2004, the quality of the data, collected in various countries, has been professionally controlled by a team of experts, making it very reliable. Because of this, this study only uses the surveys after 2004. But because the oil and gas rents data are available until 2008 only, this research would not be able to use the surveys after 2008. Hence, only surveys between 2004 and 2008 could be exploited for this study. GEM consists of 6 The evidence also shows that rise in oil and gas profits has an adverse effect on institutional quality when there is little history of good institutions. Using a panel dataset covering ninety-nine countries during 1980–2004 and controlling for income, time-varying common shocks, regional fixed-effects, and some other covariates, Bhattacharyya and Hodler (2010) find that natural resources only induce corruption in countries that have endured a nondemocratic regime for more than 60% of the years since 1956. Vicente (2010) compares changes in perceived corruption in the island Sao Tome and the island of Cape Verde which have similar histories, culture, and political institutions after a natural experiment – a significant oil discovery in the island of Sao Tome. He finds that corruption increased by close to 10% after the announcements of a significant oil discovery in 1997–99. In a quasiexperimental setting and using data on Brazilian municipalities, Fernanda Brollo et al. (2013) show that an increase in oil profits of 10% for a municipality raises corruption by 17–24%, and increases the likelihood of the incumbent remaining to office by 7%. It also shrinks the fraction of its opponents holding a college degree by 7%. All these mean that in countries with little history of good institutions an increase in oil and gas profits deteriorates the institutional quality and shifts the rents curve more towards left. 7 More information about the GEM project may be found at www.gemconsor tium.org.
two surveys: the Adult Population Survey (APS) and the National Expert Survey (NES).8 APS is a harmonized, nationally representative random population survey gathered annually from individuals in each participating country. Within country sample size ranges from 2000 to 45,000. In each country, a team is responsible for conducting the survey. A local survey firm is carefully chosen to collect data for a standard survey questionnaire. Survey questions are standard globally and conducted simultaneously across all countries between May and August of every year. Surveys are collected via phone and where phone penetration is low by door-to-door interviews. A standard protocol governs sampling, coding, weighting and other data collection procedures. A central coordination team of experts monitors the sampling procedure in each country and the accuracy and compatibility of data across countries. It requests for clarifications and corrections for coding and weightings, whenever necessary, so that the protocol would be followed by all national teams. At the end of collection procedure, the central coordination team harmonizes the data across countries, and offers them to public on the GEM consortium website.9 This study uses APS series to measure productive entrepreneurial activity for several reasons. First, APS is a population survey and asks individuals whether they engage in businesses. If the individual owns or manages a business, or is in the process of starting one, she will be asked follow-up questions about the business and herself. Therefore, it covers microenterprises which are notoriously difficult to account for in firm surveys. Second, APS accounts for informal businesses which are usually neglected in firm surveys, since firm surveys create their sample based on registered businesses. Third, APS datasets are collected according to a standard protocol across countries and are quality-controlled and harmonized by a central team. Therefore, entrepreneurial activities are measured consistently and easily comparable across countries. This is very important in cross-country comparison and is rarely the case. For example, unlike APS datasets, some economic indicators are measured differently in each country which renders them incomparable. Fourth, APS data account for those who failed as well. Failure is an important part of entrepreneurship which is usually not measured in other surveys. All these reasons make GEM surveys the best for studying entrepreneurship across countries. Data on oil and gas rents come from World Bank Subsoil and Forest Rents dataset. It has annual rents, i.e. profits, from oil and gas for every country from 1970 to 2008. These rents are divided by population to obtain rents per capita which is the most reliable measure of the significance of natural resource in an economy (For a discussion, please see Ross (2008)). Population data and GDP per capita in 2005 constant prices are from World Bank Development Indicators. Corruption Perceptions Index, which is used as a measure of corruption, is obtained from Transparency International. This study employs countries which produce oil or gas (even in small volumes) even if they are net-importers. The sample has 50 countries. Table 1 contains the summary statistics of all the variables used for this sample. GDP and oil and gas rents per capita are deflated to account for inflation. 8 NES is an expert opinion survey containing opinions about nine dimensions of entrepreneurial environment in each country. These dimensions are finance, government policies and programs, entrepreneurial education and training, R&D transfer, commercial and professional infrastructure, entry regulation, physical infrastructure and services, and cultural and social norms. This study does not employ NES surveys and only uses APS data. 9 www.gemconsortium.org; Details about the procedures used to collect and harmonize GEM data can be found in Reynolds et al. (2005). An overview is in Minniti (2011).
M. Majbouri / Energy Policy 94 (2016) 10–15 Table 1 – Summary statistics.
13
Table 2 – Entrepreneurial Activity and Resource Rents; Arellano Bond Estimations with Country Fixed Effects. Mean
Std. dev.
Min
Max
0.2 21.5 6.6 3.4 9.9 0.5 43.1
0.1 3.1 2.1 2.1 1.0 0.5 15.2
0.05 13.1 2.2 0.4 6.7 0.0 9.0
0.66 26.8 9.6 7.8 11.1 1.0 104.0
All Productive entrepreneurship rate ln(Rents per capita) Transparency International CPI Corruption index ln(GDP per capita) Female' Age
Note: Productive entrepreneurship rate shows the share of individuals in the population of the country that are productive entrepreneurs. An individual is considered a productive entrepreneur if at the time of the survey, she was engaged in starting a business, or a new venture in an existing business, or owned an established business, or had shut down a business in the 12 months prior to the survey. ln (Rents per capita) represents annual profits from oil and gas rents deflated for inflation. Transparency International CPI is the Corruption Perceptions index which is between zero (fully corrupt) and ten (no corruption). Corruption is equal to ten minus Transparency International CPI. ln (GDP per capita) and its squared are in 2005 constant prices for each country and over time. Female is a dummy equal to one if the individual is female and zero otherwise. Age is measured in years. Number of countries: 50 countries Years: 2004 through 2008.
(1)
The rest of this paper demonstrates if rents have any impact on entrepreneurial activity. Consider the following dynamic panel data model:
Hkt =αHkt −1+β ln (Rentkt ) + γ ′Zkt +ck+ + εkt
(1)
(3)
(4)
L. entrepreneurship
0.004
0.154
0.165
0.009
ln (Rentspercapita)
(0.354) 0.037nn
(0.337) 0.044nn
(0.334) 0.039
(0.304) 0.036
(0.017)
(0.017)
(0.039) 0.021n
(0.034) 0.022nn
(0.012) 0.361
(0.010) 0.094
×Corruption L. ln (GDP per capita)
(L. ln (GDP per capita))2
1.172
0.959
(1.483) 0.078
(1.246) 0.066
(1.303) 0.039
(0.981) 0.024
(0.077)
(0.066) 0.111 (0.124) 0.017 (0.015) 0.017
(0.067)
(0.052) 0.125 (0.109) 0.018 (0.014) 0.018
Female Age Age2 ×10−2
(0.014) Observations Number of countries
4. Estimation and results
(2)
58 27
58 27
(0.013) 58 27
58 27
Note: The dependent variable is a dummy equal to one if the individual is a productive entrepreneur in the past year (description in the text and notes for Table 1). L. is the lag operator. For description and summary statistics of variable, please see Table 1. 50 countries and 5 years (2004 through 2008) are in the sample. Not all countries have data for all years. Therefore, the number of countries with at least three observations required for Arellono-Bond estimation is 27. Robust-heteroskedastic standard errors are in parentheses nn
in which, Hkt is the share of entrepreneurs out of the adult population in country k in year t and Hkt − 1 is its lagged value. ln (Rentkt ), and Zkt are respectively natural log of oil and gas rents per capita, and observed characteristics of country k in year t . f (Rentkt ) is a function of Rentkt . ck is the country k fixed effect which controls for all characteristics of country k that are fixed over time. These include but not limited to culture, history, traditions, social norms, political, social and economic institutions, laws and regulations, and time-constant demographic characteristics. εkt are independently distributed disturbances. Table 2 presents the results for the least squares estimations of Eq. (1), when the dependent variable is the share of population who was a productive entrepreneur in country k and year t . In this study, a productive entrepreneur is defined as someone for whom any of the following four statements in the GEM surveys is true:
n
po 0.10. p o 0.05.
As entrepreneurship rate in a country may have a dynamic relationship with its lagged value over time, Hkt − 1 is included in Eq. (1). But including the lagged value of the dependent variable with fixed effects creates endogeneity (Nickell, 1981). The bias from this endogeneity has an inverse relationship with the number of time periods. Since there are only five years of data, the bias can be substantial. Therefore, Arellano-Bond estimator is used to instrument for lagged values of the dependent variable and consistently estimate the regression (Arellano and Bond, 1991). Like GDP per capita, oil and gas rents per capita has a large variation across countries. Hence, similar to GDP per capita, one can use natural log of oil and gas rents per capita. As Fig. 2 shows,
You are, alone or with others, currently trying to start a new
business, including any self-employment or selling any goods or services to others. You are, alone or with others, currently trying to start a new business or a new venture for your employer – an effort that is part of your normal work. You are, alone or with others, currently the owner of a company you help manage, self-employed, or selling any goods or services to others. You have, in the past 12 months, sold, shut down, discontinued or quit a business you owned and managed, any form of selfemployed, or selling goods or services to anyone.
The fourth statement is particularly necessary to be included as failure is an important part of entrepreneurship. One of the strengths of GEM surveys is that they account for those who failed as well. Note that GEM, like any other survey of entrepreneurship, only measures productive entrepreneurship which is all we need for this study. From now on, we refer to productive entrepreneurship when we mention entrepreneurship.
0.25
0.2
0.15
0.1
0.05
0
0
10 20 ln(Real rents per capita + 1)
30
Fig. 2. Distribution of natural log of oil and gas rents per capita. Note: real rents per capita is the total profits (price minus the cost of production) of oil and gas in constant prices deflated and divided by population of the country.
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M. Majbouri / Energy Policy 94 (2016) 10–15
the distribution of this variable is discontinuous between 0 and 13. About twenty percent of the observations have the value of zero and the rest are above 13. Only countries with non-zero oil and gas rent are used in the sample. Table 2 reports the regressions based on Eq. (1) for the whole sample. The first column has lagged values of the dependent variable, L. entrepreneurship, log of rents per capita, and country fixed effects. It also contains lagged values of log of GDP per capita and its squared, important predictors of entrepreneurship rate in a country. Lagged values of GDP per capita are used since current values could create simultaneity. Consistent with the theory discussed in Section 2, the coefficient of log of rents per capita is negative. The size of the coefficient implies that doubling oil and gas rents reduces productive entrepreneurship rate by about 4 percentage points. In the second column, some country characteristics like the average age of the population and its squared as well as sex ratio of the population (i.e. female) are included. Age and gender are strongly correlated with the probability of individuals engaging in entrepreneurial activity. The negative coefficient of rents remains robust both in statistical significance and size. These results are robust to many omitted variables. Lagged value of the dependent variable, L. entrepreneurship, controls for any dynamic relationship in entrepreneurship over time. Interestingly, the coefficient of this lagged variable is insignificant in all columns, suggesting that there is no dynamic relationship in these regressions. The country fixed effects control for any feature of a country that is constant over time. Therefore, all time-constant factors including but not limited to history, culture, religion, social norms, time-constant traits and attitudes, political and economic institutions, time-constant laws and regulations, do not bias the results. There might still be country-specific time-varying factors that would be correlated with GDP and rents per capita as well as entrepreneurial activity, and hence, bias the results. It is not possible to control for such factors with country-time fixed effects as rents vary across country and time. Based on the theory explained in Section 2, one may argue that the impact of oil and gas rents should be larger in countries that are more corrupt. In order to test this conjecture, one can interact oil and gas rents with a measure of corruption in the country. Transparency International measures corruption globally every year and reports it in an index called Corruption Perceptions Index which is between 0 (the most corrupt) and 10 (the least corrupt). In other words, the larger is this measure, the less the country is corrupt. In order to get a measure that is increasing in corruption, one can subtract Corruption Perception Index from 10. This way the least corrupt environment gets a zero grade and the most corrupt one is marked 10. This new variable, entitled Corruption, is included in the regressions to simplify the interpretation of the results. Columns (3) and (4) of Table 2 report these results using the sample of oil or gas producers. We observe that the negative impact of oil and gas rent only exists when there is corruption and as corruption increases, productive entrepreneurship is discouraged more. Interestingly, the impact of oil and gas rents when corruption does not exist is positive but statistically insignificant. In other words, profits from oil and gas has positive or no impact on productive entrepreneurship in countries such as United Kingdom, Canada, and Norway, which have very low corruption. The turning point is roughly at corruption index of 2.
5. Conclusion and policy implications This study offered the first empirical evidence for the inverse relationship between the size of oil and gas rents and productive entrepreneurship. This relationship is only pronounced in a
corrupt environment. Profits from oil and gas boost productive entrepreneurship, especially in a less corrupt environment, as they offer new opportunities through creating a new industry (oil and gas), as well as increasing disposable incomes and demand for new products and services. But when corruption exists, more income for the governments, through owning or taxing oil and gas resources, creates opportunities for rent-seeking. This entices potential entrepreneurs to choose rent-seeking rather than productive entrepreneurship because it is more lucrative. Therefore, productive entrepreneurship declines. One important lesson for policy is that in developing countries, where corruption is prevalent, oil and gas rent may not be advantageous for the economy and specifically productive entrepreneurship. It creates new sources of rents, thereby increasing the expected returns to rent-seeking activities. One solution is to reduce the amount of rent that is available to the government. Ideas such as transparent commodity funds, and lump-sum distributions are helpful in reducing rent-seeking. Governments can create transparent sovereign wealth funds to save some of the oil and gas profits especially when those profits are rising and new rent-seeking opportunities are created. Since these savings take excess profits out of the economy and into the transparent fund, fewer new opportunities for rent-seeking will be created when the oil and gas profits increase. Another way to reduce rent-seeking activities is to distribute all excess profits from oil and gas among the general public. This is the idea based on Alaska Permanent Fund which by law distributes half of investment earnings, equally among the population. As a result, less rent becomes available for rent-seekers.10 Another important lesson is that fighting corruption and creating more transparency is the key in harnessing natural resources. Since these profits can become a source of corruption and bad institutions themselves,11 it is difficult to mix oil and gas with transparency but the resulting potion is the elixir of fast and continuous growth. One solution is that the whole process of extraction, transportation, refinement, and revenue management of oil and gas is audited by international auditors. Joining the Extractive Industries Transparency Initiative (EITI) provides a standard framework for governments, and the industry alike, on how to reduce corruption. Grass-roots pressure in the developed countries have pushed the international corporations to sign off on social responsibility schemes such as EITI by which they have to follow stricter rules in dealing with resource-rich governments. Under the EITI initiative, the oil companies need to publish what they pay to governments and the governments need to show their receipts. The initiative matches these two figures and publishes the result for the general public. Wenar (2008) argues that governments in very corrupt but resource rich countries that are appropriating oil and gas revenues are in fact stealing it from their citizens. Therefore, the multinational corporations who are involved in the process of discovery, extraction, transportation, and refinement with these governments can be held accountable for dealing with them and legal action should be pursued against them where there is strong rule of law (such as The United States or Europe). This discourages these multinational corporations from doing business with the corrupt governments and encourages the states to enact reforms and pursue institutional change. The problem with this approach, 10 Sala-i-Martin and Subramanian (2013) and Birdsall and Subramanian (2004) suggest this idea for Iraq and Nigeria. El-Anshasy et al. (2015) offer detailed policy suggestions in this arena. Majbouri (2015) calculated the opportunity cost of not following the Hartwik rule (as the best policy) for the economies of oil producing countries in the Middle East and North Africa region. 11 See Bhattacharyya and Hodler (2010) for panel data evidence, Vicente (2010) and Borello et al. (2010) for quasi-experimental evidence.
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he acknowledges, is that corporations that operate outside jurisdictions with strong rule of low, such as Chinese corporations, are immune to these legal actions. Wenar, however, proposes “anti-theft tariffs”, on for instance Chinese exports to Western countries, equal to the size of business with those corrupt governments. The collected tariffs will later be transferred to the citizens of those countries as soon as minimum standards of institutional reforms are in place. This solution, however, may trigger a global tariff war and the result is not beneficial for anyone. Another solution is to establish an international organization like WTO (or its predecessor GATT) that oversees and governs involvements of all internationally active corporations in extractive industries. This organization should be formed through multilateral negotiations between governments of all countries that have extractive industries which operate globally. The goal will be to form multilateral agreements on the structure and mechanism of disputes and punishments for breaching ethical rules of doing business with corrupt governments of resource-rich countries. This international institution can be part of existing institutions such as WTO. The agreements should be comprehensive and need to be ratified by all parties. Like climate change and environmental degradation, this is an issue that needs global initiative and commitment. The punishment may not turn out to be as severe as one would hope for but this new institution will provide more transparency in the process and clearly depicts to citizens of those countries how their governments and international corporations use revenues from their natural resources. More research and innovative ideas are required to solve this global problem. In addition to these issues, one interesting fact to note is that some government policies that try to encourage entrepreneurship, are themselves becoming a source of rent-seeking activity. For instance, governments sometimes sponsor entrepreneurs, subsidize their cost of capital, labor, or reduce their taxes. There are also many government sponsored competitions that choose entrepreneurs and give them awards or special treatments. But, these policies usually become a source of rent for rent-seekers themselves, and lead to worse outcomes. The issues of adverse selection and moral hazard are prevalent in these cases. Many potential entrepreneurs write proposals or define projects just to acquire these rents from the government. It is always difficult for governments to choose the winners, the right entrepreneurs and the right projects. In many cases, projects that are not feasible or economical but attractive and extravagant have a higher chance of being chosen (adverse selection). This results in many bad apples wasting resources. In addition, entrepreneurs who enjoy these benefits have less incentive to work as hard and attain success (moral hazard). More research on understanding the interrelation of oil and gas and corruption is necessary and more ideas to encourage entrepreneurship that are feasible in developing countries are required.
Acknowledgements I am sincerely grateful to the editor and the reviewer of Energy Policy for the thoughtful comments and helpful suggestions. My thanks also goes to Babson Faculty Research Fund (BFRF) for the financial support of this research and to Candida Brush, Donna J. Kelley, Maria Minniti, and BFRF reviewers for their comments. All the remaining errors are mine.
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