Project: FREE policy brief
Environmental Implications of Russia’s Accession to the WTO
Authors: David G. Tarr, NES and Natalia Turdyeva, CEFIR.
We investigate the environmental impacts of Russia’s World Trade Organization (WTO) accession with a computable general equilibrium model incorporating imperfectly competitive firms, foreign direct investment and endogenous productivity. The WTO accession affects CO2 emissions through technique (−), composition (+) and scale (+) effects. We consider three complementary policies to limit CO2 emissions: cap and trade, emission intensity standards, and energy efficiency standards. With imperfectly competitive firms, gains from WTO accession result with any of these policies.
Taxes and Benefits in the Polish Parliamentary Election Campaigns
Authors: Michal Myck and Monika Oczkowska, CenEA.
The upcoming parliamentary elections in Poland, scheduled for the 25th of October 2015, have on the one hand stimulated debate on the record of the current coalition government, and on the other opened the debate on the nature of socio-economic policy to be conducted in the coming years. In this brief, we draw on two recent pre-election reports published by the Centre for Economic Analysis, CenEA. We discuss developments in tax and benefit policies under the coalition of the Civic Platform and the Polish People’s Party over the last eight years, as well as the pre-election pledges regarding tax and benefit policies to be implemented after the elections. We show a significant shift in policy priorities with respect to the distributional effect of the tax-benefit policies between the first (2007-2011) and the second (2011-2015) term in office, towards more support for low-income families. We also argue that, judging by the presented electoral pledges, Polish voters face a difficult choice between the promises of the opposition parties, which seem too costly to be realistic, and an enigmatic tax overhaul reform proposed by the governing Civic Platform, which is supposed to substantially benefit nearly all working households at a low cost for the state budget, with details of the reform design, however, kept away from public scrutiny.
Russia: Increasing Concentration of the Economy and Low Investment
Author: Oleg Shibanov, New Economic School and Corporate University of Sberbank.
The Russian economy became more concentrated in 2014. The new RBC-500 rating shows that the 643 largest companies in Russia produce 77% of the country’s GDP. Moreover, 94% of the net profit of these companies was generated in the oil and gas sector. This is up from 71% in 2013. This increasing concentration appears unstable at times of huge external shocks on commodity prices.
Does Gender Matter for the Innovativeness of SMEs?
This policy brief summarizes the results of an on-going research project on the gender aspect of companies’ innovativeness in transition countries. The aim of this work is to examine whether there is a gender gap in innovative behavior within the sector of small and medium-sized enterprises (SMEs). The results suggest that the propensity to innovate is higher among companies with a presence of a female owner. This finding preserves for 5 measures of innovativeness. Thus, female involvement in business might be beneficial for the innovative sustainable development of economy.
The role of small and medium-sized enterprises (SMEs) has increased lately and they are considered one of the main engines of economic growth (Radas and Bosic, 2009). Research on transition economies and development has emphasized the need for strong a SME sector, since it often acts as the backbone of the economy (Lukasc, 2005) and is the largest contributor of employment (Omar et al., 2009). Another important channel through which the SME sector contributes to development is through their innovative activities. Sustainable economic development requires competitive and successful industries. Being innovative is one way to achieve this goal. However, the innovativeness of sectors and industries depends not only on the actions of the largest companies, but also on the SME sector and individual entrepreneurs. Indeed, the latter are often argued to be more dynamic and more ambitious (Chalmers, 1989; Li and Rama, 2015).
The decision to follow an innovative strategy often depends on the company’s leader, their experience and other managerial characteristics. However, the experience of the leader is not the only factor affecting managerial actions – gender also appears to matter (Daunfeldt and Rudholm, 2012). In the absence of clear answers and knowledge about female managerial characteristics, including their innovativeness (Alsos et al., 2013), it is difficult to evaluate their role in modernizing the business society and to distinguish their competitive advantages or disadvantages over male managers and business owners.
The role becomes even more ambiguous for the transition, post-communist economies. The labor market under USSR officially provided equal rights to women. However, in practice women were treated differently than men. While women often had to do the same work as men, the patriarchal society remained with men being regarded as the main decision makers, and women being fully responsible for housework and childcare. This can explain the low presence of women in top-managerial positions and women’s weaker business ties and networks (Welter et al., 2004).
The question of gender and innovation in entrepreneurship has recently starting to attract attention. Earlier, innovativeness was strongly connected and associated with high-tech companies. Thus, innovation research mostly focused on technology-based and capital-intensive industries (Dauzenberg, 2012; Marlow and McAdam, 2012). As a result, innovation behavior in less capital-intensive SMEs was almost entirely overlooked. This can also explain the lack of focus on gender, as men usually dominated the capital-intensive industries (Ljunggren et al., 2010). In an ongoing research project, I am trying to expand the understanding of gender differences in innovation and SME entrepreneurship with a focus on transition economies and the CIS block in particular.
The idea is to estimate owners’ and CEOs propensity to implement innovations in the organization. The specification of the model follows the literature and uses a probit technique that allows for an estimation of these propensities while taking into account other influencing factors and individual characteristics of firms, their owners and CEOs, which likely affect innovative decisions. The data I use come from the 5th wave of the Business Environment and Enterprise Performance Survey (BEEPS) conducted in 2012-2013. The final dataset covered 5254 SMEs from 30 European and East Asia countries.
The main variable of interest is the innovativeness of the enterprise, proxied by 5 different indicators. The measures of implemented innovative activities are: 1) whether the firms introduced a new product or service during the last 3 years; 2) whether there was any new production process implemented; 3) whether there were any spending on research and development; 4) whether were was an introduction of a new marketing strategy and method; and 5) whether an enterprise implemented new methods in operational management. The usage of 5 indicators instead of one allows me to see whether there is any specific feature of innovativeness that differs by gender.
The list of control variables covers information on the gender of the CEO and owners, number of years of experience of the CEO, age of the firm, type of ownership, focus on internal and external markets, as well as the usage of foreign technologies and certification. I also have information on the share of skilled labor force, the share of females in the organization, and whether the organization bears additional costs on external consulting services and training of employees. Information on industry, country, size of the organization and type of residence is also available.
Unfortunately, the data lacks information on the number of owners, which will prohibit me from estimating the clear gender effects and limits the analysis to the effect of gender diversity among owners.
The obtained results (see Table 1) show that having a female as the only, or one of the, owner(s) increases the propensity of going into uncertainty and implementation of a new good/service by 4.5% in the CIS region and 6.7% in the non-CIS block. However, the effect of having a female CEO is insignificant. This finding contradicts the literature on gender differences in the willingness to take on risk (Wagner, 2001; He et al., 2007; Eckel et al., 2008; Croson and Gneezy, 2009) that mostly demonstrates that women, on average, are more risk-averse than men.
A similar effect is observed for the implementation of a new business process or marketing strategy. The only insignificant difference is the spending on R&D in CIS countries and new managerial methods in non-CIS block. However, these measures of innovativeness raise doubts regarding its applicability for SME sector. A shift from high-intense productions towards services makes it less useful to spend enormous sums of money on technological research. Instead, other innovative actions like the development of human capital are of greater importance.
Table 1. Propensity to innovate
Source: Author’s own estimation.
Conclusion
The results show that having a female owner or gender diversity in the ownership structure positively affects the propensity of the organization to follow innovative behaviors and strategies. Therefore, promoting female entrepreneurship and gender equality in ownership seem positive for increasing the innovativeness of companies, and the economy in general, in both the CIS and non-CIS block.
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References
- Alsos, G.A., Hytti, U., and Ljunggren, E. 2013.Gender and Innovation: State of the Art and a Research Agenda.International Journal of Gender and Entrepreneurship, 5(3):236-256.
- Chalmers, N. 1989. Industrial Relations in Japan: The Peripheral Workforce. London: Routledge.
- Croson, R. and Gneezy, U. 2009. “Gender Differences in Preferences”.Journal of Economic Literature.Volume 47, #2.
- Daunfeldt, S., O., and Rudholm, N., (2012). Does gender diversity in the boardroom improve firm performance? Department of Economics, Dalarna University, SE-781 88 Borlänge, Sweden; and HUI Research, SE-103 29 Stockholm, Sweden.
- Dautzenberg, K. 2012. Gender differences of business owners in technology-based firms.International Journal of Gender & Entrepreneurship,4:79–98.
- Eckel, C. and Grossman, P. 2008. “Men, Women and Risk Aversion: Experimental Evidence”. Handbook of Experimental Economic Results.Elsevier.Volume 1, #7.
- He, X., Inman, J.J. and Mittal, V. (2007), “Gender jeopardy in financial risk taking”, Journal of Marketing Research, 44: 414-24.
- Li, Y., and Rama, M. 2015. Firm Dynamics, Productivity Growth, and Job Creation in Developing Countries: The Role of Micro- and Small Enterprises. The World Bank Research Observer, 30: 3-38.
- Ljundggren, E., Alsos, G.A., Amble, N., Ervik, R., Kvidal, T., Wiik, R. 2010. Gender and innovation: Learning from regional VRI projects. Nordland Research Institute, Norway.
- Lukacs, E. 2005. The economic role of SMEs in world economy, especially in Europe. European Integration Studies, 4(1): 3-12.
- McAdam, M. and Marlow, S. 2008.The Business Incubator and the Female High-Technology Entrepreneur: A Perfect Match? Paper presented at the 2008 International Council for Small Business World Confrence, recipient of the 2008 Best Paper Award for Women Entrepreneurship.
- Omar, S. S., Arokiasamy, L., & Ismail, M. 2009. The background and challenges faced by the small and medium enterprises. A human resources development perspectives. International Journal of Business and Management, 4(10): 95-102.
- Radas, S., and Božić, Lj. 2009.The Antecedents of SME Innovativeness in an Emerging Transition Economy. Technovation, 29: 438-450.
- Wagner, M.K. (2001), “Behavioral characteristics related to substance abuse and risk-taking, sensation-seeking, anxiety sensitivity and self-reinforcement”, Addictive Behaviors , Vol. 26, pp. 115-20.
- Welter, F., Smallbone, D., Isakova, N., Aculai, E. and Schakirova, N. 2004. Social Capital and Women Entrepreneurship in Fragile Environments: Does Networking Matter? Paper presented at Babson College-Kauffman Foundation Entrepreneurship Research Conference, University of Strathclyde.
Leniency, Asymmetric Punishment and Corruption: Evidence from China
Since coming into office two years ago, Chinese President Xi Jinping has carried out a sweeping, highly publicized anticorruption campaign. Skeptics are debating whether the campaign is biased towards Mr. Xi’s rivals, and even possibly related to the current economic slowdown. What is less debated is the next stage of Mr. Xi’s anti-corruption strategy, which is going to alter the legal statutes. Amendment IX, proposed in October 2014, includes heavier penalties, but two important tools in the fight of corruption – one-sided leniency and asymmetric punishment – became more limited and discretional. We argue that studying a 1997 reform and its effects can shed some light onto why the Chinese leadership seems dissatisfied with the current legislation and the likely effects of the proposed changes.
What We Know about Leniency
In our context, leniency can be defined as the concession of reduced sanctions (or full immunity) to wrongdoers that cooperate by self-reporting and providing information against former partners in crime. Formal and informal exchanges of leniency against information and collaboration are normal features of law enforcement in most countries. Policies of this kind have been extensively and quite successfully used to fight the Italian and American mafias, drug dealing and other organized crimes, and have become the main instrument to fight collusion in antitrust since the US reform in 1993 (see Spagnolo, 2008).
For crimes in which multiple offenders cooperate, one-sided leniency conditional on being the first to self-report can be a very powerful tool of law enforcement: by playing the partners in crime against each other, it may elicit information, greatly facilitate prosecution and generate deterrence at a very low cost. A conspicuous scientific literature with theoretical, experimental and empirical contributions shows the great potential of these policies, when properly designed and administered, for deterring collusive crimes (Miller 2009; Spagnolo 2008; Bigoni et al. 2012, 2015). On the other hand, Buccirossi and Spagnolo (2006) show specifically for the case of corruption that, when poorly designed or administered, these same policies may become ineffective or even counterproductive.
Asymmetric Punishment
A related way of using leniency towards one party (to play it against the other) in the fight against corruption has been at the center of a recent intense policy debate after the popular note “Why, for a Class of Bribes, the Act of Giving a Bribe Should Be Treated as Legal”, by Kaushik Basu (2011). Then chief economist of the Indian government and now of the World Bank, Basu advocated asymmetric depenalization of bribe giving, which can be thought of as a form of unconditional, one-sided leniency. More precisely, the note proposed to legalize bribe giving in the form of harassment bribes (also called extortionary, or discharge-of-duty bribes) paid to obtain something one is entitled to, while strengthening sanctions against bribe taking. As with other forms of leniency, the idea is to create a conflict of interests between the partners in crime by increasing the temptation for one party to betray and report the illegal act, leading to a severe punishment of the other.
In the debate sparked by this note many different arguments have been put forward, both against it and in favor of it. Dufwenberg and Spagnolo (2015) discuss formally some of the issues raised by critics of the proposal, while Abbink et al. (2014) provide (mixed) experimental evidence on its effectiveness. Later, a blogpost by a Chinese law scholar, Li (2012), attracted our attention to the case of China, where asymmetric punishment (bribe-giver impunity) has been in place since 1997. She argued, probably reflecting the political debate in the country rather than based on factual evidence, that the system had not been successful. We felt this claim granted a deeper investigation into the details of the Chinese legal reform and the changes it introduced, and of course a careful inspection of the data to back it.
A Study in Red
In a new working paper, Perrotta Berlin and Spagnolo (2015), we set out to understand the evolution of the anti-corruption legislation in China over the last decades, and then to evaluate the effects of the policy changes occurring in 1997. Two new elements were given the strongest legal status in 1997: leniency for wrongdoers that self-reported and cooperated with investigators, and asymmetric punishment (no charge for bribe givers) for bribes paid to obtain something one was entitled to. Concurrently, penalties were decreased, in particular for bribe-takers.
To understand the likely effects of this policy change we would ideally look at correspondent changes in corrupt transactions. Data on the prevalence of bribery, however, are notoriously hard to come by because of the secretive nature of this activity. Instead, we use several data sources which capture on the one hand actual corruption cases tried in courts, and on the other hand surveys of corruption perceptions. In particular, we have collected the number of arrests and public prosecutions on the counts of corruption and bribery from the Procuratorates’ Yearly Reports for each Chinese province since 1986.
It is not straightforward to infer changes in total corruption, which is unobserved, from changes in discovered cases tried in court. The data on prosecutions mix together corruption and anticorruption activities, as they fail to distinguish occurrence of the criminal activity from detection. A policy that deters crimes but at the same time increases the fraction of those that are successfully prosecuted will have an ambiguous effect on the number of prosecutions. We adapt for this purpose the testable predictions developed by Miller (2009): he models the occurrence of criminal activity (cartel formation, in this case) and derives predictions for how changes in the rate of occurrence and the rate of detection affect the time series of detection.
The preliminary evidence we have so far points to a substantial and stable reduction in the number of major corruption cases around the 1997 reform, a result consistent with a positive deterrence effect of the 1997 reform. The evidence is suggestive, and some alternative interpretations of the patterns in the data, shown in the plot below, cannot be excluded at the moment. While a peak-and-slump pattern as in Miller (2009) would have been much stronger evidence supporting the success of the reform at deterring corruption, we cannot exclude that the drop in prosecutions is simply due to a general worsening in detection. Although we deem this unlikely in the light of the general political climate of the time, we need more and better data to support our interpretation. Still, claims that the reform did not have an effect appear not supported by the data.
Figure 1. Change in Corruption Prosecutions before and after law reform in 1997
Source: Perrotta-Berlin and Spagnolo (2015).
More to be done
A case study analysis is under way to corroborate and help the interpretation of these preliminary findings. We will analyze in depth a stratified random sample of prosecution case files between 1980 and 2010. Given that we sample a given number of cases, in this part of the analysis we cannot gain any insight about the incidence of bribery in general. We can instead observe the impact of the legislative reform on specific details of the corrupt behavior, and the mechanisms through which this behavior occurs or is deterred. In particular, we will be able to distinguish between cases of extortionary (harassment) bribes and bribes paid to obtain illegitimate benefits. Moreover, this will allow us to shed light on whether and how leniency and asymmetric punishment were applied in practice. The details of the case files might even allow us to gain insight into how the bribe-size and the value of corrupt deals evolved through the reform and even the selection into bureaucracy.
Conclusion
One-sided leniency, conditional on reporting an act first, or unconditional, as when bribe giving is depenalized, may be powerful corruption deterrence instruments if well designed and implemented in the right environment, but may also have negative effects. It has been argued that these instruments have been ineffective in China, after they were reformed in 1997, however, without data supporting the claim. Part of the reason lies in the difficulty to obtain good data on corruption. Another obstacle is the subtlety of interpreting them when they relate only to detected and convicted cases, rather than to the whole population of corruption cases.
We cannot solve completely the issue of data quality, as we also need to rely on official reports of counts of corruption cases. However limited, the exercise performed on aggregated data clearly shows that the 1997 Criminal Law reform did have an effect, consistent with increased corruption deterrence. To further support this finding we will collect and analyze micro-data from a randomized sample of these cases. This will allow us to isolate at a higher level of detail the changes in criminal behavior, reporting behavior and prosecution activity, and link them to the details of the legal reform to highlight the mechanisms at work.
China is home to a sixth of humanity, and currently undergoing a massive crackdown on corruption. Whatever we can learn about the effectiveness of their past and present anti-corruption policies is likely to have considerable welfare effects. Moreover, the 1997 reform was the object of a policy debate, and comments on its effectiveness came without data to support them. We believe our effort to use data to shed light on what this reform actually changed will be a valuable input to further research and policy discussion on this important topic.
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References
- Abbink, K., U. Dasgupta, L. Gangadharan, and T. Jain. “Let-ting the Briber Go Free: An Experiment on MitigatingHarassment Bribes.” Journal of Public Economics, 111,2014, 17–28.
- Basu, K. “Why, for a Class of Bribes, the Act of Giv-ing a Bribe Should Be Treated as Legal.” WorkingPaper 172011 DEA, Ministry of Finance, Governmentof India, 2011
- Bigoni, M., S.-O. Fridolfsson, C. LeCoq, and G. Spagnolo.“Fines, Leniency and Rewards in Antitrust.” RANDJournal of Economics, 43, 2012a, 368–90.
- Bigoni, M., S.-O. Fridolfsson, C. LeCoq, and G. Spagnolo.. “Trust and Deterrence.”. Journal of Law, Economics, and Organization (2015)
- Buccirossi, P., and G. Spagnolo. “Leniency Policies and Ille-gal Transactions.” Journal of Public Economics, 90,2006, 1281–97.
- Buccirossi, P., Marvão, C. M. P., & Spagnolo, G. (2015). Leniency and Damages. Available at SSRN 2566774.
- Dufwenberg, M. and Spagnolo, G., Legalizing Bribe Giving (April 2015). Economic Inquiry, Vol. 53, Issue 2, pp. 836-853, 2015.
- Li, X. Guest post: bribery and the limits of game theory – the lessons from China. http://blogs.ft.com/beyond-brics/2012/05/01/guest-post-bribery-and-the-limits-of-game-theory-the-lessons-from-china/, 2012. Accessed: 2015-05-20.
- Miller, N. H. Strategic leniency and cartel enforcement. The American Economic Review, pages 750–768, 2009.
- Perrotta Berlin, M. and G. Spagnolo, Leniency, Asymmetric Punishment and Corruption: Evidence from China, SITE Working Paper, 2015 (forthcoming)
Evaluating the Political Man on Horseback – Coups and Economic Development
In a new paper (Meyersson, 2015) I examine the development effects of military coups. Coups overthrowing democratically elected leaders imply a very different kind of event than those overthrowing autocratic leaders, and these differences relate to the implementation of authoritarian institutions following a coup in a democracy. Although coups taking place in already autocratic countries show imprecise and sometimes positive effects on economic growth, in democracies their effects are distinctly detrimental to growth. Moreover, when coups overthrow democratic leaders, they fail to promote economic reforms, stop the occurrence of economic crises and political instability, as well as have substantial negative effects across a number of standard growth-related outcomes including health, education, and investment.
Do military coups matter for economic development? After all, successful coups – i.e. where the military or state elites have unseated an incumbent leader – have occurred 232 times in 94 states since 1950 (see Figure 1). Moreover, around a quarter of these overthrew democratically elected governments (Powell and Thyne, 2012). The prevalence of military coups has not been lost on researchers, yet despite an abundance of research aiming to explain the occurrence of coups (see for example Acemoglu and Robinson, 2001; Collier and Hoeffler, 2006 & 2007; Leon, 2014; Svolik, 2012) much less research has focused on its economic effects (two exceptions are the papers on covert US operations during the Cold War by Dube, Kaplan, and Naidu, 2011 and Berger, Easterly, Nunn, and Satyanath, 2013). Olsen (1963), for example, claimed that coups “often bring no changes in policy.” Londregan and Poole (1990), in their panel-data analysis, find no effects of coups on income.
By now, there is mostly a consensus that significant military influence in politics is detrimental for democracy (Dahl, 1971; Huntington, 1965; Linz and Stepan, 1996). Nonetheless, military coups overthrowing democratically elected governments are often met with ambiguity. Western governments have a long history of tacit support for military coups overthrowing democratic governments, be it left-leaning governments in Latin America or Islamist governments in the Middle East and North Africa (Schmitz 2006). Commentators expressing support for coups often do so invoking extreme outcomes to represent the counterfactual to the military coup; if Pinochet had not overthrown President Allende, the latter would have created a Castro-style regime in Chile; if the Algerian army hadn’t annulled the elections in 1992, the Islamist FIS would have turned Algeria into an Islamist dictatorship in the Maghreb, and so on (Los Angeles Times 2006, Open Democracy 2013). Similarly, the fault for the coup and preceding problems fall invariably upon the ousted leader, with the coup constituting an unfortunate, but necessary, means to rid the country of an incompetent, if not dangerous, leader (Foreign Policy, 2013).
Other commentators have pointed out the risks of allowing a military to intervene and dictate post-coup institutions to their advantage; a “Faustian” bargain likely to bring regime stability but no solution to the real underlying problems behind the conflict in the first place. Yet others lament the human rights abuses following coups, and the inherent ineptitude of military leaders in running the economy (NYT, 2013; New Republic, 2013; Washington Post, 2013).
Figure 1. Successful and Failed Coup Attempts by Country and Year
Notes: The graph shows successful (solid circles) and failed coup attempts (hollow circles) by country and year, and aggregated by country (right graph) as well as by year (top graph). A circle in blue means the political regime was classified by Cheibub et al 2010 as a democracy in the year before the attempt and a red circle means they classified the regime as an autocracy.
Military coups tend to be endogenous events, and establishing a causal relation between coups and development is therefore a challenge. The unobservable likelihood of a coup – often referred to as coup risk (Collier and Hoeffler, 2006 & 2007; Londregan and Poole, 1990; Belkin and Schofer, 2003) – may be driven by many factors also affecting a country’s development potential, such as weak institutions, the military’s political power, social conflict, and economic crises etc.
In order to address this problem, I employ several empirical strategies including comparing successful versus failed coup attempts, matching methods, as well as panel data techniques, using a dataset of coup attempts during the post-World War II era. These methods facilitate, in different ways, comparisons of development consequences of coups in situations with arguably more similar degrees of coup risk.
Of significant importance is distinguishing coups when they occur in clearly autocratic settings from those where they overthrow democratically elected governments. I show that a military coup overthrowing a regime in a country like Chad may have very different consequences than a military leader overthrowing a democratically elected president in a country like Chile. In the former, a coup appears to constitute the manner in which autocracies change leaders. In the latter, coups typically imply deeper institutional changes with long-run development consequences.
I find that, conditional on a coup-attempt taking place, the effect of coup success depends on the pre-intervention level of democratic institutions. In countries that were more democratic, a successful coup lowered growth in income per capita by as much as 1-1.3 percent per year over a decade. In more autocratic countries, I find smaller and more imprecisely estimated positive effects. This effect is robust to splitting the sample by alternative institutional measures, as well as to a range of controls relating to factors such as leader characteristics, wars, coup history, and natural resources. As Figure 2 illustrates, the economic effect of coups tend to worsen over time. Extending the analysis to matching and panel-data methods reveal these results to be highly robust.
Figure 2. Relationship between a Successful Coup and Growth in GDP per capita
Notes: The three graphs represent the coefficient on a successful coups on growth in GDP per capita (PPP) between year t-1 and t+s with s given by the x-axis for all regimes(left), autocracies (middle), and democracies (right). Controls include period t-1 values of log GDP per capita, annual growth, log population, PolityIV index, annual change in the PolityIV index military expenditures as a share of GDP, annual change in military exp/GDP, military personnel as a share of population, years since the last coup, total number of previous coups, social unrest, leader tenure, as well as continent and year dummies respectively. See Meyersson (2015) for details.
A commonly held view is that coups overthrowing democratically elected leaders often provide an opportunity for engaging in unpopular but much needed economic reforms. Not only do I show that coups fail at this, but also that they tend to reverse important economic reforms, especially in the financial sector, while also leading to increased indebtedness and an overall deteriorating net external financial position, and an increased propensity to suffer severe economic crises. A documented reduction in social spending suggests a shift in economic priorities away from the masses to the benefit of political and economic elites.
Whereas coups occur mostly in dire situations, their prescriptions, as shown, rarely constitute adequate remedies to the underlying problems, as the institutional changes brought by these events show clear detrimental development consequences. Any short-lived benefit of regime stability a coup brings, comes at a steep economic, political, and human cost in the longer run.
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References
- Acemoglu, Daron and James A. Robinson, “A Theory of Political Transitions,” The American Economic Review, Vol. 91, No. 4 (Sep., 2001), pp. 938-963
- Berger, Daniel, William Easterly, Nathan Nunn, and Shanker Satyanath. 2013. ”Commercial Imperialism? Political Influence and Trade during the Cold War.” American Economic Review, 103(2): 863-96.
- Belkin, Aaron, and Evan Schofer, 2003,“Toward a Structural Understanding of Coup Risk”, Journal of Conflict Resolution, Vol. 47 No. 5, October 2003 594-620
- Cheibub, Jos ́e Antonio, Jennifer Gandhi, and James Raymond Vreeland, 2010, “Democracy and dictatorship revisited,” Public Choice (2010) 143: 67-101.
- Collier, Paul and Anke Hoeffler, 2006, “Grand Extortion: Coup Risk and the Military as a Protection Racket,” working paper
- Collier, Paul and Anke Hoeffler, 2007, “Military Spending and the Risks of Coups d’ ́etat,” working paper.
- Dahl, Robert A., Polyarchy: Participation and Opposition, Yale University Press 1971.
- Dube, Arindrajit, Ethan Kaplan, and Suresh Naidu, “Coups, Corporations, and Classified Infor- mation”, Quarterly Journal of Economics, Quarterly Journal of Economics, 2011 (Vol. 126, Issue 3)
- Foreign Policy, “Blame Morsy,” Michael Hanna, July 10 2013,
- Huntington, Samuel P., 1965, “Political Development and Political Decay,” World Politics, 386- 429
- Leon, Gabriel, 2014, “Loyalty for Sale? Military Spending and Coups d’Etat,” Public Choice 159, 363-383
- Linz, Juan, and Alfred Stepan, Problems of Democratic Transition and Consolidation: Southern Europe, South America, and Post-Communist Europe, Johns Hopkins University 1996
- Los Angeles Times, “Iraq needs a Pinochet”, Jonah Goldberg, December 14, 2006
- Londregan, John B and Kenneth T. Poole, “The Coup Trap, and the Seizure of Executive Power,” World Politics, Vol. 42, No. 2 (Jan., 1990), pp. 151-183
- Meyersson, Erik, 2015, Political Man on Horseback – Military Coups and Development, working paper, http://erikmeyersson.com/research/
- Olsen, Mancur, “Rapid Growth as a Destabilizing Force,” The Journal of Economic History, Vol. 23, No. 4 (Dec., 1963), pp. 529-552
- Open Democracy, February 11 2013, https://www.opendemocracy.net/arab-awakening/hicham-yezza/how-to-be-different-together-algerian-lessons-for-tunisian-crisis.
- Powell, Jonathan M, and Clayton L Thyne, 2012, “Global instances of coups from 1950 to 2010: A new dataset,” Journal of Peace Research 48(2) 249-259
- Schmitz, David F. “The United States and Right-Wing Dictatorships”, Cambridge University Press 2006
- Svolik, Milan W., The Politics of Authoritarian Rule, Cambridge University Press 2012.
- The New Republic, “Egypt Officially Declares What Is and Isn’t Important”, Nathan J. Brown, July 9 2013, http://www.newrepublic.com/article/113792/egypt-president-adli-mansour-makes-constitutional-declaration.
- The New York Times, “A Faustian Pact: Generals as Democrats”, Steven A. Cook, July 5, 2013
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Non-Tariff Measures in the Context of Export Promotion Policies
This brief focuses on the role of non-tariff measures (NTMs) in international trade. While multilateral and bilateral trade negotiations have resulted in worldwide reductions in tariffs, we observe an increasing trend in the application of non-tariff measures. In this brief, we will discuss the evidence of the effect of such measures on exports. The brief also contributes to the discussion of export promotion policies: whether governments, especially in developing countries, should concentrate their efforts to remove only external barriers since there is empirical evidence that internal barriers are no less important for exports.
Economists, policy makers and international organizations are increasingly recognizing the importance of non-tariff measures (NTMs) as substantial impediments to international trade. A survey conducted by UNCTAD among exporters in several developing countries ranks SPS and TBT measures the top trade barriers with on average 73 percent of the respondents viewing them as the primary trade barrier (UNCTAD 2010). The World Bank published a book on NTBs where different authors contributed chapters addressing many aspects of the NTMs (World Bank, 2012). The World Trade Organization (WTO) itself devoted its entire 2012 World Trade Report to such measures with a particular focus on technical barriers to trade (TBT) and sanitary and phytosanitary (SPS) measures. Availability of the new datasets on NTBs allowed researchers to study the effect of these measures on intensive (changes for existing exports) and extensive margins (changes due to entry and exit into exporting) of trade.
Even though trade theory does not specifically address the question of non-tariff barriers that include (but are not limited to) technical regulations, sanitary and phytosanitary measures, the logic of traditional models can easily be extended to these measures. In particular, they can be thought of as part of the fixed/additive costs for exporting firms as they impose compliance costs on exporters. These compliance costs are related to potential adjustments of production processes, and certification procedures needed to meet the requirements of countries imposing such regulations and standards (Schlueter et al., 2009). In a Melitz-type model, these costs are expected to have a negative impact on volumes of trade, number of exporters and number of goods exported. At the same time, average exports per firm may actually increase as the export market-shares are reallocated towards firms that are more efficient.
The existing empirical evidence of the impact of NTMs is mixed; researchers have found both positive and negative effects. The differences in results depend largely on the sector, country and type of NTM imposed. While the effect may overall be negative or null, for some sectors the effect is found to be positive (Moenius, 2004; Fontagné et al., 2005; Chen et al., 2006; Disdier et al., 2008; Medin and Melchior, 2015).
In a recent working paper, Besedina (2015) investigates the effect of introducing an NTM (either SPS or TBT) on export dynamics (in particular, exports concentration and entry and exit into exporting) using the World Bank Exporters database, with a special focus on trade in foodstuff. In particular, we examine how TBT and SPS measures affect export concentration and diversification (both at product and destination level) as well as entry and exit of firms into exporting. If introduction of an NTM increases costs of exporting, the ‘new’ trade theory started by Melitz (2003) predicts that some exporters will stop to export and thus the number of exported product varieties will fall as well (change in extensive margin).
The most important result from our analysis is that the introduction of a TBT or an SPS measure does not seem to affect sectoral export dynamics. Given the above discussion, this result may appear surprising at first. What can possibly explain this zero effect?
First, one may argue that the sector dynamic variables we use in our analysis may not capture changes in the behavior of economic agents (firms) well: while marginal firms may be affected by technical barriers and SPS, averaging across firms may actually conceal this. However, in our analysis we investigate exports at a relatively disaggregated level (4-digit product lines). So while averaging might be a concern, we believe it is not likely to be driving the zero effect.
Second, the concern is that the effect of introducing an NTM measure may not be felt immediately (within one year). In order to verify this, we include lagged trade-barrier variables two periods, but the results were unchanged. Third, it may be the case that it is the number of NTMs rather than the introduction of them that matters. In order to address this point, we performed the same type of analysis using the change in the number of measures introduced. The results were again not affected, and we still do not find any statistically significant relationship between NTMs and exports dynamics.
Despite the absence of an effect of NTMs, this paper reveals an important and policy-relevant finding: the home country’s business environment and institutional factors are important determinants of export performance. It is rather the monetary costs and more complicated exporting procedures imposed by the NTM measures that hamper product and market diversification of the country’s exporters. Hence, policy makers, especially in developing countries, should not only be concerned with removing external barriers to exports (like NTMs) but should also aim to reduce internal barriers and costs imposed on exporting firms by corrupt practices and burdensome regulatory procedures.
Another important dimension for domestic policies towards exporters stems from the work by Melchior (2015, forthcoming) who studies Norwegian exports to BRICS countries overtime and shows that export growth largely depends on the intensive margin (it explains 93 percent of the export growth). Using firm-level data for seafood exports, he finds that only 54% of “trades” – measured as firm/importing country/product combinations – survive from one year to the next. Hence, there is massive “churning” (entry and exit at the same time), and churning is relatively more important in small and in growing export markets. In other words, exporting companies constantly enter and exit foreign markets, add new products, or discontinue exporting some products. A policy implication from this finding is that export-promotion offices should help firms stay in export markets rather than focus on entering these markets. Hence, while it is important to enable domestic firms to enter foreign markets, it seems equally important to ensure their survival in foreign markets, which can be facilitated by a removal of both external and internal barriers.
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References
- Disdier, A-S, L. Fontagné and M. Mimouni (2008), “The Impact of Regulations on Agricultural Trade: Evidence from the SPS and TBT Agreements”, American Journal of Agricultural Economics 90(2): 336-350.
- Fontagné, L., F. von Kirchbach, and M. Mimouni (2005). “An Assessment of Environmentally-related Non-tariff Measures”, The World Economy 28(10): 1417-1439.
- Medin H. and A. Melchior (2015) ”Trade barriers or trade facilitators? On the heterogeneous impact of food standards in international trade”, NUPI mimeo
- Melchior (2015) ” Non-tariff barriers, firm heterogeneity and trade: A study of seafood exports, with a particular focus on BRICs”, NUPI mimeo
- Melitz, M. J. (2003), “The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity,” Econometrica, 71(6): 1695–1725.
- Moenius, J. (2004), “Information versus Product Adaptation: The Role of Standards in Trade”, Working Paper, International Business & Markets Research Center, Northwestern University mimeo.
- UNCTAD (2010), Non-Tariff Measures: Evidence from Selected Developing Countries and Future Research Agenda (UNCTAD/DITC/TAB/2009/3). New York and Geneva.
- World Bank (2012), Non-Tariff Measures – A Fresh Look at Trade Policy’s New Frontier, ed. O. Cadot and M. Malouche, The World Bank, Washington D.C.
Export Costs of Visa Restrictions
We study the role of visa restrictions in determining export flows between firms and countries, and find a significant negative impact of visa restrictions. Our results indicate that visa costs not only diminish the value of export, but also the probability of new firms to enter visa restricted foreign markets. We interpret these results as evidence that visa restrictions contribute to trade costs faced by exporting firms.
There is no doubt that policy decisions in the area of foreign relations influence economic links between countries. However, quantifying these effects is usually very difficult – not least because visa regimes are relatively stable over time, not allowing for sufficient variation to estimate the effect of a regime change. As a result, decision-making is often based on very limited quantitative grounds, and mostly driven by qualitative intuition and strong political preferences. However, these decisions might have very important redistributive effects and create unequal access to markets for producers from different countries. For example, while WTO emphasizes a nondiscrimination clause to be one of the main principles of trade policies for member countries, foreign policy might become a very important source of discrimination in international trade.
An example of such policy decisions is visa requirement for foreign visitors. The channel of the effect is rather intuitive – visa requirements on foreign nationals might affect the intensity and costs of business visits needed to establish trade relations between firms in different countries.
In Kapelko and Volchkova (2015) we test the impact of foreign visa requirements on the international trade based on the Russian case. The Russian economy represents a unique setting to study the effect of visas on trade flows. Over the first decade of 2000, there were more than 30 visa regime changes between Russia and foreign countries. Thereby, there is sufficient variation for quantifying the export costs of visa restrictions.
Evidence
Economists observe that when a pair of countries has visa restrictions – both bilateral and unilateral – their bilateral trade flows, tourist exchanges, and FDI flows are smaller compared to pairs of similar countries without these restrictions (Neumayer, 2011). The anecdotal evidence also indicates that business meetings, conferences and other interactions which involve people from different countries are often cancelled or delayed due to the failure of some participants to obtain visa stamps on time. Therefore, we can assume that costs of visas for international transactions include not only simple monetary costs associated with the visa fee but also less predictable components such as the risk of refusal, time costs, etc.
Economic research often relies on some intrinsic features of goods or industries as a way to test the hypothesis. Namely, if the extent of the studied effect depends on these features then one would compare the effects across goods or industries controlling for the features. In our case, if the effect of visas is due to risks associated with the inability of businessmen to attend meetings or negotiations, then we can expect a negative effect of visa restrictions on trade flows, which will be stronger for goods trade since it requires more interactions between the buyer and seller. For this study, we rely on Rauch’s (Rauch, 1999) definition of relation specific goods and compare the effect of visas across goods with different degrees of sensitivities to the relations.
Method
The recent developments in trade theory and empirical research provide a specification of structural relations between country-level bilateral costs of trade and firm level decision to export. The heterogeneous firms approach brought by Marc Melitz (Melitz, 2003) to the international trade framework emphasizes that fixed costs of exporting play an important role in shaping patterns of exports. The literature distinguishes between fixed and variable costs of exporting, but the empirical evidence on cost composition is very limited and very little is known so far about the fixed costs of exporting. We proxy both these costs with visa restrictions, and use heterogeneity in firms’ decisions whether to export or not, to various destinations, to estimate the effect of visas on market access and trade flows.
Data
We combine annual data on exporters, volume of export of each exporter to each destination from the Russian Customs Transaction Database with data on all bilateral visa constraints for the period 2003-2010 between Russia and 180 foreign export destinations.
First, we test whether Russian firms export less to countries which impose strict visa restrictions compared to countries with less restrictive visa regimes or visa waiver programs, other things being equal. We test these effects separately for trade in goods which are more specific to the parties involved in the transaction (relation-specific goods, such as manufactured goods, and equipment with specific technical requirements on part of buyer) and trade in goods that depend less on the parties involved in the transactions (non-relation specific goods, such as more homogeneous, standard goods) (Rauch, 1999). Then, we estimate the effects of visa restrictions on the value of trade to chosen destinations.
The obvious concern is that visa decisions are dependent on trade. Politicians might facilitate visa negotiations if the country’s economic interests expand toward some destinations. It might for example affect visa waivers between countries. To deal with this issue we use tourist flows between countries as an instrument to allow for more accurate measurement of visa effects.
Our empirical strategy is to use the two-stage least squares approach with weighing in the second step to eliminate the potential bias due to selection into exporters to particular destination (Imbens and Wooldridge (2009)).
Results
Our results indicate that visas have a strong negative effect on market access, and it is twice as high for export of relation-specific goods as for export of non-relation specific goods. Controlling for the choice of destination, visas have a significant negative effect on the value of exports of relation-specific goods as well.
More specifically, our estimations indicate that:
- the probability of the firm to export to visa-restricted destinations is below the probability of export to visa-free destinations. The probability gap is estimated to be about 36 percent for the overall sample, 40% for relationship specific transactions and 26% for non-relationship specific export.
- the value of exports for relation specific goods is negatively affected by visa restrictions while there is no effect of visa restrictions on the export of non-relation specific goods. Our estimations indicate that the effect of visa is quite substantial so the value of relation specific export is twice as low to visa restricted as to visa free destinations.
These results emphasize the economic importance of visa restrictions and they are consistent with the assumption that visa restrictions do, in fact, contribute to the costs of market access. The negative effect of visa restrictions on the value of exports of relationship specific goods indicates that they also contribute to the variable costs of export.
Conclusions
The implications of this analysis may be very important. It demonstrates that visa regimes play a role as a non-tariff restriction or as a barrier, and can have significant effects on the development of trade relations between countries. The losses in trade due to visa restrictions are both extensive and intensive in nature: fewer firms are engaged in trade between countries with strong visa restrictions and they trade less in terms of more sophisticated goods. Therefore, we document at least two types of distortions in trade flows due to visas: visa distorts trade relations across countries with different visa requirements, and visa distorts trade flows across different types of goods to destinations with different visa requirements. Given the substantial negative effects of visas on trade relations, it is worth accounting for these economic costs when Ministries of Foreign Affairs engage in negotiations toward visa waivers.
References
- Helpman, E., M. Melitz, and Y. Rubinstein. 2008. Estimating Trade Flows: Trading Partners and Trading Volumes. Quarterly Journal of Economics, Vol. 123 No2, 441-487.
- Imbens, G., and J. Wooldridge . 2009. “Recent developments in the econometrics of program evaluation”. Journal of Economic Literature, 47(1) pp5-86
- Kapelko, N., and N. Volchkova. 2015. “Export costs of visa restrictions”, CEFIR Working Paper, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2243136
- Melitz, M. J. 2003. “The impact of trade on intra-industry reallocations and aggregate industry productivity.” Econometrica 71(6).
- Neumayer, E. 2011. “On the Detrimental Impact of Visa Restrictions on Bilateral Trade and Foreign Direct Investment.” Applied Geography 31 (3): 901–907.
- Rauch, J. E. 1999. “Networks Versus Markets in International Trade.” Journal of International Economics 48 (1): 7–35.
The Role of Belarusian Private Sector
The development of a private sector and the expansion of its role in the economy is one of the key goals repeatedly announced by the Belarusian authorities. The reforms carried out in Belarus in 2006-2014 moved the country from 106th to 57th position in the World Bank Doing Business ranking. The official statement is that reforms boosted the rapid development of business initiatives and its impact on economic development. Unfortunately, there is no clear confirmation of this statement. The absence of a transparent and clear methodology in Belarusian statistics on how to evaluate the role of the private sector makes it difficult to evaluate the exact input of the Belarusian business in the economy and compare its role to other countries.
In the last 5 years, the Belarusian authorities have repeatedly highlighted the need to develop the private sector, perceiving it as the main source for sustainable economic growth and competitiveness of Belarus in the future.
However, it may be difficult to assess the real role of the private sector in the Belarusian economy. First, existing data do not allow a clear identification of the boundaries between the private and state-owned sectors in Belarus. Furthermore, there are certain methodological differences in identifying and evaluating the private sector between Belarusian official statistics, the World Bank approach and alternative methodologies. These methodological variations combined with data limitations result in significantly different estimates of the role of the private sector for the Belarusian economy. The problem concerns both the evaluation of the role of small and medium enterprises (SMEs) and the private sector in general.
Small and Medium Enterprises
One good example of the abovementioned data issue is the statistics for SMEs sector. Unlike the EU, Belarus does not include individual entrepreneurs to the micro organizations in the SME sector. This results in highly different estimates for the number of SMEs per 1000 inhabitants (Figure 1). If we follow the methodology of the National Statistical Committee of the Republic of Belarus (Belstat), the number is 9.7 firms per 1000 people. However, switching to the EU methodology (IFC report, 2013) raises the number significantly up to 35.9. Moreover, the inclusion of unregistered self-employed individuals involved in the shadow economy (which according to estimations of the authorities amount to at least 100,000 inhabitants) increases the number to 46.5 firms per 1000 people, which is above the level of many European countries.
Figure 1. SME density
Source: own estimations from Belstat data, Eurostat.
Private Sector
As for the private sector in general, the problem here is that the official statistics counts enterprises with mixed form of ownership and state presence to the private sector. This makes it difficult, if at all possible, to obtain the exact input of the private sector to the economy and see the dynamics of its change.
More specifically, there are three potential ways to assess the contribution of the private sector. Unfortunately none of them provides reliable estimates of the role of business. The first method is to use official data. The main problem here is that the private sector according to official statistics includes enterprises with state presence as well as large private companies that are under state control and not totally independent. Thus, the contribution of the private sector calculated based on these figures is likely overestimated.
The second method is to look at enterprises that do not report to the Belarusian ministries, following the methodology of the World Bank used in their evaluation of Belarus machinery industry (Cuaresma et al., 2012). Here, non-ministry reporting enterprises work as a proxy for a private firm, as in this case it doesn’t have to report directly to Belarusian ministries and is independent from the state.
The problem is that the majority of large private enterprises, even though there is no state share in them, are not in this list. In Belarus these enterprises often form a part of state concerns on the one hand and are independent on the other. The example here is JSC “Milavitsa”, one of the largest lingerie producers in EE, which is a part of the Bellegprom concern. Therefore, this methodology likely underestimates the role of the private sector.
The third way is to try to exclude state presence from the official data of the private sector. According to official statistics, the private sector includes several groups of enterprises, such as individual entrepreneurs, legal entities with/without state/foreign presence, etc. However, the absence of a clear distinction between these sub-groups allows for only rough estimates, through the extraction of the state presence.
As a result, all obtained numbers are qualitatively different from each other and there is no clear answer if any of them reflects the real picture.
For example, the contribution of the private sector in total employment according to the three different methods (Figure 2) provides the following results. Officially, in 2013 around 53% of the active labor force worked in the private sector. However, the exclusion of state presence in private property changes the results significantly and the share of the active labor force involved in the private sector drops to a level of 31%, while the non-ministry reporting enterprises employ around 18% of the active labor force.
Figure 2. Private sector in employment (%)
Source: own estimations from Belstat data.
The input of the private sector in the total production volume (Figure 3) is also very diverse depending on the method of evaluation. Official data show that the private sector is responsible for 80% of total production volume. However, the exclusion of state presence decreases the value to a level of just 26%, which is similar to the result demonstrated by the non-ministry reporting enterprises (25%).
Figure 3. Private sector in total production volume (%)
Source: own estimations from Belstat data.
At the same time, the absence of a clear definition of the private sector does not allow for obtaining reliable information about its effectiveness. If we take the rate of return on assets (ROA), again, there is a significant gap in the results of the different methods of estimation (Figure 4). ROA of the private sector according to official statistics is significantly lower than similar indicators based on the data obtained by the other two methods (in 2013: 1.17 vs. 2.4 and 1.3 respectively). Thus, the lower the “measured” state presence, the higher is the productivity of the private sector, especially in comparison with the effectiveness of the state sector (0.25).
Figure 4. Return on Assets (BYR/BYR)
Source: own estimations from Belstat data.
Conclusion
The above discussion has illustrated that diffuseness of data and the definition of the private sector is likely to create troubles for understanding the importance of the private sector in Belarus. This, in turn, may undermine the effectiveness of economic and political measures targeted towards this sector.
The implementation of a clear, unified and transparent methodology of how to estimate the role of business and what exactly can be treated as a private sector in statistics would allow for a better understanding of the obstacles and barriers that the private sector is dealing with, as well as to help developing effective measures of business support. Until then, the official statistics should not stick to just one definition of the private sector. Instead, it can use all three abovementioned gradations, as a better reflection of the realities of Belarusian business.
References
- Cuaresmo, J., Oberhofer, H., Vincelette, G. (2012).‘Firm Growth and Productivity in Belarus: New Empirical Evidence in the Machine Building Industry’, World Bank, Policy Research Working Paper No. 6005.
- ‘Business Environment in Belarus 2013.Survey of Commercial Enterprises and Individual Entrepreneurs’, IFC, Report.
Meeting Qualification Mismatch with Vocational Training
While in an ideal world the qualification preferences of job seekers and employers would coincide, in reality this is often not the case. Besides informational asymmetries (job seekers not knowing which qualifications are demanded by employers) the reason is that employers may be in need of qualifications that are not considered attractive by the job seekers. In the country of Georgia, we want to address this problem through a “recommendation system” which will suggest vocational training to job seekers. There are two main problems to be tackled in this project: (1) How can we decide what would be the most useful qualification for a given job seeker, and (2) how can we incentivize the job seekers to follow our recommendations? This policy brief discusses our approach to this problem.
Introduction
Qualification mismatches are common in many labor markets around the world (see for example, Ghignoni and Verashchagina (2014) for Europe, McGuinness and Sloane (2011) for the UK, and Béduwé and Giret (2011) for France). It is well known that qualification mismatch is a relevant problem also in the country of Georgia, as was shown in various studies (see ISET (2012) and The World Bank (2013)).
The ISET Policy Institute (ISET-PI) was commissioned by the World Bank to assist the Social Service Agency (SSA) of Georgia, an agency of the Ministry of Labor, Health, and Social Affairs, in developing a system which will recommend vocational training to job seekers with the aim to reduce the qualification mismatch in Georgia.
Job Seekers’ Preferences Matter
Vocational training addresses the needs of two different groups. It is demanded by job seekers, who want to improve their human capital in a way that matches their preferences and, in the optimal case, maximizes their chances to get back into employment. At the same time, vocational training also addresses the needs of employers, whose businesses may face shortages in qualified personnel.
It is not enough to only include employers in the analysis if one wants to effectively fight the qualification mismatch. If one does not consider job seeker’s preferences, it may happen that people prefer to not participate in the vocational training system at all. Even if one can effectively incentivize job seekers to attend training programs, as is the case in Germany for example, where the refusal to participate in training is sanctioned by a reduction of unemployment benefits (cf. Neubäumer (2012)), it is likely that involuntary training will be less effective. Therefore, it is problematic that most studies which analyze the demand for qualifications in the job market, for example for the European Union (Lettmayr and Nehls (2012)), New Zealand (Earle (2008)), and Australia (Shah (2010)), exclusively focus on employers and neglect the preferences of the people who are to be trained. In Georgia, we will do it differently.
Why Would Job Seekers Follow Our Recommendations?
The objective of the recommendation system we develop is to maximize the impact the training has on the employment chances of the job seeker. Arguably, this is also the primary goal for most job seekers, as they often state that they want to receive training in an “employable” profession. Therefore, if the purpose of the recommendation system is communicated properly, and if it is transparent and trustworthy, the job seekers may want to voluntarily follow its advice.
Recommendation System vs. Matching Algorithm
One can think of two different ways of advising job seekers in their training choices: recommendation systems and matching algorithms.
Recommendation systems make suggestions to job seekers separately. These kinds of systems are ubiquitous on the Internet. For example, Amazon.com proposes books to its customers based on their purchasing history. In a similar way, a recommendation system for vocational training would suggest vocational training programs to job seekers based on relevant data about their characteristics and the job market situation. Yet its major shortcoming is that a recommendation system will not take into account what other job seekers do and what recommendations were given to them.
For that reason, in a recommendation system, it can happen that the number of people recommended to choose a certain program is larger than that program’s capacity (because the advice comes as a ranking, this does not cause the system to be useless, as the job seeker may then choose the program which is highest in the ranking and which has free places).
Likewise, if many job seekers follow the advice of the recommendation system, oversupply and undersupply of certain qualifications in the job market is not ruled out. This is again due to the fact that recommendations are made separately. If there is a huge demand for, say, plumbers, and many people receive the advice to receive training in plumbing, this may subsequently cause an oversupply of plumbers.
In contrast, a matching algorithm aims at an overall optimum for the whole group of job seekers. Genuine matching algorithms do not make separate recommendations, but propose a globally optimal assignment. In Western countries they are used, for example, to match interns to hospitals, students to universities, and kidneys to dialysis patients. Matching theory is one of the most successfully applied subfields of game theory, acknowledged through the award of the Economics Nobel Prize of 2012 to matching theorist Alvin E. Roth. The standard survey of matching theory is Roth and Sotomayor (1990).
In a matching algorithm, the abovementioned problems of a recommendation system would not occur (up to statistical uncertainty), because the matching algorithm would take into account how the suggestions made by the system affect the demand for a program. It would aim to keep the number of people, likely to choose a program, to remain below its capacity.
While a matching algorithm is more ambitious, it also has disadvantages compared to a simple recommendation system. First of all, the data requirements are higher, as the capacities of programs have to be taken into account. More importantly, in a matching algorithm the recommendations will be generated in a way that is not transparent to the job seeker (though it is possible to give some general explanations). This may reduce acceptance and willingness to participate. The recommendation system, on the other hand, can work in a relatively transparent way. Finally, a recommendation system can be adjusted and changed on an ongoing basis by Social Service Agency personnel without the help of external experts. Given its complexity, this is hardly possible with a matching algorithm.
Therefore, it was decided that the simpler option of a recommendation system is to be pursued. Later, the system may be upgraded to a full-blown matching algorithm.
The Technical Aspects of How Recommendations are made
Consider the situation of a job seeker looking for vocational training. Through the envisioned system, they will receive a recommendation of which qualification to pick in the vocational training system of the SSA.
The pieces of information used for making this recommendation are personal characteristics of the job seeker (like age, gender, preferences, skills, and other information obtained through the website worknet.ge which is operated by the SSA) and the current and future economic situation in different sectors. To this end, we will use value added tax data that can be decomposed into 45 sectors and updated on a monthly basis. For forecasts, we will draw on the Business Confidence Index of ISET, which allows decomposition into 5 sectors.
Given the information about the job seeker and the economic environment in different sectors, we will answer the question: “How many months do we expect the job seeker to be unemployed in the year after the training if the training was in qualification X?” Here, X can be whatever is offered in the vocational training system at the location of the job seeker, for example welder, mechanic, accountant, or IT expert. Alternatively, we could answer the question: “What is the salary we expect the job seeker to have in the year after the training if the training was in qualification X?”
The recommendation made to the job seeker will be: “Choose the training in field X if somebody with your personal characteristics, given the economic situation and outlook, has the lowest expected number of unemployed months (or the highest salary) in X in the year after training in X was received.” This recommendation is likely to be accepted by the job seeker if also the job seeker wants to maximize their employment chances (or maximize salary).
The forecast can be made using econometric regression analysis. Let i be a job seeker and xi be the number of months unemployed in the year after training was received. Then we have for each qualification one estimation equation
where alpha is the intercept and the betas are the coefficients for different personal and economic characteristics. When the alpha and beta coefficients are known, then one can enter the specific data for a job seeker and forecast how long it would take him to find a job if training would be received in a particular field.
For estimating the coefficients, no recommendations will be made for some time (like 3 months) after the system is launched and only information will be collected. The SSA or a specialized survey agency will call the job seekers every month after they received training and ask whether they found employment. Job seekers who received training through the SSA will be obliged to answer this question truthfully. Information about the characteristics of the job seeker is known through their participation in the worknet.ge system, which is a requirement for anybody who wants to receive vocational training through the SSA.
When the recommendation phase starts, further data will be collected. Errors in the estimation of the coefficients will be corrected “automatically” through the feedback (in terms of job market performance of the trainees) that the system gets on an ongoing basis. To increase this effect, the database used for the estimation of the coefficients will be “rolling”, i.e. people who recently received training will be added while those who received training a longer time ago (e.g. one year or more) will be removed from the database.
Conclusion
In Georgia, ISET will design and implement a recommendation system for vocational training, addressing the qualification mismatch in the labor market. As in many other areas, Georgia is willing to go for innovative policy solutions making use of advanced economic methods, very much in line with the country’s reputation as one of the top reformers in the world.
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References
- Béduwé, Catherine and Giret, Jean-Francois (2011): “Mismatch of vocational graduates: What penalty on French labour market?”, Journal of Vocational Behavior 78, pp. 68-79
- Earle, David (2008): “Advanced trade, technical and professional qualifications: Matching supply to demand”, New Zealand Government Ministry of Education, Auckland.
- Ghignoni, Emanuela and Verashchagina, Alina (2014): “Educational qualifications mismatch in Europe. Is it demand or supply driven?”, Journal of Comparative Economics, in press
- ISET (2012): “National Competitiveness Report for Georgia”, Tbilisi.
- Lettmayr, Christian F. and Nehls, Hermann (2012): “Skills supply and demand in Europe: Methodological framework”, CEDEFOP Working Paper No. 25
- McGuinnes, Seamus and Sloane, Peter J. (2011): “Labour market mismatch among UK graduates: An analysis using REFLEX data”, Economics of Education Review 30, pp. 139-145
- Neubäumer, Renate (2012): “Bringing the unemployed back to work in Germany: training programs or wage subsidies?”, International Journal of Manpower 33, pp. 159 – 177
- Roth, Alvin E. and Sotomayor, Marilda (1990): “Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis”, Econometric Society
- Shah, Chandra (2010): “Demand for qualifications and the future labour market in Australia 2010 to 2025”, Center for the Economics of Education and Training Working Paper, Monash University
- The World Bank (2013): “Georgia: Skills Mismatch and Unemployment Labor Market Challenges”, World Bank Report No. 72824-GE