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GEO-ECONOMICS
Michael P. BARRY
Ph.D., J.D., Assistant Professor of Economics, Mount Saint Mary’s University (Emmitsburg, Maryland, U.S.A.).
POST-SOVIET MIGRATION TO RUSSIA: A COMPUTABLE GENERAL EQUILIBRIUM APPROACH
Abstract
Immigration laws or lack of laws in the former Soviet Union have led to a large migration of workers from Central Asia and other former Soviet republics into the Russian Federation. Economic theory would predict that, other things being equal, real wages in Russia would fall while real wages in the other republics would tend to rise. At the same time, it is sometimes argued that a significant brain drain has hurt the other former Soviet Republics while the
Russia Federation has gained. This paper outlines the fundamentals of Russian migration policy after the breakup of the Soviet Union, and uses a computable general equilibrium model (CGE) to analyze the effects on wages, economic growth, and trade between Russia and the other republics. Results show that while millions of people moved from other former Soviet republics to Russia, the net effect on the region’s macroeconomic picture was minimal.
I n t r o d u c t i o n
U.N. data suggests that a net total of 1.1 million people in the other 14 republics of the former Soviet Union migrated to the Russian Federation shortly after the breakup of the U.S.S.R. What would the economies of these nations be like today had this migration not occurred?
THE CAUCASUS & GLOBALIZATION
The question requires a counterfactual analysis, meaning there is no going back to the past. Many, many things have happened in the former Soviet Union since the 15 republics broke apart at the end of 1991. Any model that pretends to capture all of those events seems over-ambitious. A more limited question is the “ceteris paribus” question: leaving all other things equal, what was the effect of the migration alone? That is what this paper attempts to do.
Using a massive database created by a consortium of universities and government agencies, a computable equilibrium model is employed. Such a model tries to account for all economic sectors and regions of the world simultaneously. With equilibrium in all markets across the world, the model asks what a shock (like a migration flow) would do to that equilibrium.
The following paper attempts to measure the effect of this migration. To do this, several sections are included:
(1) a brief history of the post-soviet history of Russia;
(2) a look at the dramatic changes in Russian demography;
(3) a discussion of Russian migration law;
(4) a summary of CGE modeling in general;
(5) a summary of the CGE model employed in this paper;
(6) results of the model; and
(7) policy implications.
Brief Historical Background: Russia
After the collapse of the Soviet Union in 1991 in the largest republic, the Russian Federation, President Yeltsin moved quickly to introduce an economic transition plan, designed with the help of Western economists. Yeltsin’s “shock therapy” freed prices, liberalized the exchange rate, and privatized thousands of state-owned enterprises. The government struggled to cut expenditures to match its loss in revenues, traditional trade routes between former Soviet republics collapsed, and both foreign and domestic investment spending on infrastructure and capital goods disappeared. With a few years, Russian GDP had fallen by as much as 60 percent, and the population learned to live with less.
Despite a major currency crisis and default on domestic debt in 1998, the Russian economy today is in much better shape, much in part because of higher oil and natural gas prices in the global markets. A middle class has emerged in the larger cities, and the country has found a new confidence behind the leadership of Vladimir Putin. Serious questions remain, however, about the distribution of wealth, economic dependence on natural resources, democratic freedoms, and a shrinking and aging population. It is the last question posed which concerns this paper.
Russian Demography Changes
Migration to Russia is part of the larger issue of population decline. Barring a dramatic increase in the birth rate (which no one anticipates), a decline in the Russian population is inevitable because of the low birth rate of the 1990s, combined with the current high death rate. Immigration can help
alleviate the drop, but it is unlikely to reach the levels (nearly 1 million per year) necessary to offset the decline.1
Russia’s population was 149 million people in 1992; it declined by 6 million as of 2003 to an estimated 143 million (see Fig. 1). If current trends persist, the country’s population is expected to decline by over 30 percent during the next 50 years, as all measures of demographic processes show that Russia will undergo further dramatic changes in its population dynamics. The average annual population growth during 1990-2003 was -0.3 percent, and continued high mortality and declines in fertility are expected to lead to further negative population growth.2 It is estimated that the population of Russia would be 17 million higher than at present if age-specific mortality rates in Russia had followed the patterns experienced by the European Union-15 countries (EU-15) since the mid-1960s.3
Figure 1
Russian Population (thousands)
The population decline can be explained both in terms of lower fertility rates and higher mortality rates in Russia. Russia is among many countries with total fertility rates below the replacement level of 2.1 children per woman of reproductive age. In the early 1960s, Russia’s total fertility rate stood at approximately 2.6. The fertility rate dropped to about 2.2 in the late 1980s, fell below replacement in the early 1990s, and in 2000-2005, it was 1.1. Projections suggest that Russia’s total fertility rate will remain below replacement beyond 2025.4
1 See: A.C. Kuchins, Alternative Futures for Russia to 2017: A Report of the Russia and Eurasia Program, Center for Strategic and International Studies, November 2007, p. 11.
2 See: United Nations Statistics Division, International Migration Statistics, available at [http://unstats.un.org/unsd/ demographic/sconcerns/migration/default.htm].
3 See: “Dying Too Young: Addressing Premature Mortality and 111 Health Due to Non-Communicable Diseases and Injuries in the Russian Federation,” World Bank, Europe and Central Asia Human Development Department, December 2005, p. 4, available at [http://go.worldbank.org/W4TL6EAEP1].
4 See: Ibid., p. 4.
On the other side of the coin, Russia is one of the few countries in the world where life expectancy is falling. By the early 1960s life expectancy in the Soviet Union had nearly reached that of the United States, but death rates increased significantly during 1965-1985. By 1980, the difference in life expectancy was nearly 8 years. Mortality briefly slowed during Gorbachev’s early campaign against alcohol in 1985-1987, but these gains were temporary. The collapse of the Soviet Union and the transition to a market economy was accompanied by a dramatic increase in mortality. Life expectancy improved by three years between 1995 and 1998, but the gains eroded following the 1998 financial crisis, and male life expectancy fell to the current level of 58 years. Total life expectancy at birth in Russia at 66 years lags behind that of Japan by as much as 16 years and the European Union average by 14 years.5 The changing birth rates and death rates in Russia are presented in Fig. 2.
Figure 2
Births and Deaths in Russia (thousands)
3,500 -
3.000 -2,500 -
2.000 -1,500 -1,000 -
500 0
5
5
a>
1
I
0
5
cn
EH Births per year. EH Deaths per year.
S o u r c e: United Nations.
While overall population growth is negative, net migration to Russia has been positive since the breakup of the Soviet Union. In fact, more migrants have been entering Russia than leaving since the late 1970s (see Fig. 3). Net migration inflow increased during the perestroika and glasnost years of Gorbachev, as 308,000 immigrants (net) came to Russia.6 With the breakup of the Soviet Union, net migration inflows into Russia measured 453,000 during 1990-1995 and 439,000 during 1995-2000.7
5 See: “Dying Too Young: Addressing Premature Mortality and Ill Health Due to Non-Communicable Diseases and Injuries in the Russian Federation,” p. 5.
6 See: United Nations, U.N. Statistics Division, International Migration Statistics.
7 See: Ibidem.
Figure 3
Net Migration into Russia (thousands)
While migrants from nations all over the globe came to the Russian Federation in the post-Soviet period, the vast majority of people have been from the 14 other former Soviet republics.
Migration within the former Soviet Union is very complex, considering there were 53 different ethnic homelands. Fifteen became independent sovereign states, while others gained the status of special autonomous regions within one of these states. According to the World Bank, migration in the early years of the transition period in the former Soviet Union was dominated by these ethnic causes, sometimes called “diaspora” migration.8
After this initial period, migration in the former Soviet Union appears to be motivated by economics. The World Bank reports that the most recent labor flows in Europe and Central Asia (ECA) region seem largely to be: a response to poorly functioning labor markets, insufficient productive capital, the low quality of life in a number of migration sending countries, and a rising demand for unskilled labor for the nontraded services sector in the labor-importing economies in the European Union (EU) and Commonwealth of Independent States (CIS). As the neoclassic or Harris-Todaro approach argues, differences in real income or expected income clearly drive the supply of migration in a large number of cases.9
The net result is a large foreign-born population residing in the Russian Federation. In 14 of the 15 former Soviet republics, the native ethnic group’s share of the domestic population increase. Only Russia experienced a decrease in its ethnic Russian population.10 While migration was significant, this
8 See: A. Mansoor, B. Quillin, Migration and Remittances: Eastern Europe and the Former Soviet Union, World Bank, Europe and Central Asia Region, 2006, p. 79.
9 See: Ibidem.
10 See: Ibidem.
Figure 4
Nationality Composition of Migration to Russia, 1989-2003 (thousands of people)
decrease is probably more due to low birth rates and high mortality rates of the native Russian population. Fig. 4 presents the nationality composition of migration to Russia during the period 1989-2003.
Russian Migration Law
The Soviet government used strict border controls and internal residency permits (propiska) to restrict migration into the country and within the U.S.S.R. itself. Residence permits were also restricted for “undesirable elements” and ex-convicts, who wens prevented from making their homes in Russia’s largest cities. Without a propiska, people could not work, rent an apartment, marry, or send their children to school.11
Despite reform efforts to abolish the rigid propiska system, the Russian Federation continues to strictly regulate who can live where in the country. In the transition period, one leading force behind efforts to eliminate these controls were economic considerations. According to Noah Rubins of Harvard Law School, Russian leaders versed in the realities of the capitalist system also realized the detrimental economic effect of a continued propiska system. While continued restrictions may prevent a mass exodus from the impoverished countryside and relatively inhospitable North and East, studies suggest that free movement of labor is an important component in the transition from a command economy to a market system.12
The Russian Federation introduced a Federal Law on the Legal Status of Foreign Citizens in the Russian Federation in 200213. This law, under Art 37, requires foreign citizens to obtain migration cards on entering the country which are valid for 90 days.
11 See: N. Rubins, “The Demise and Resurrection of the Propiska: Freedom of Movement in the Russian Federation,” Harvard International Law Journal, Spring 1998, p. 547.
12 See: Ibidem.
13 Federal Law No. 115-Fiz of 25 July, 2002 on the Legal Status of Foreign Citizens in the Russian Federation (with Amendments and Additions of 30 June 2003; 22 August and 2 November, 2004).
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Migration cards do not entitle the holders to any benefits but must be kept with them at all times. If foreign citizens are not granted a temporary right to reside in the country they are obliged to leave under Art 5.2 of the Law after the three month period. For those groups already resident in Russia the new law has particularly serious consequences, as the foreign citizen status attributed to them is only valid for three months, however it can take up to six months under Art 6.4 to obtain a temporary residence permit valid for three years. Such persons may therefore either leave the country or be forced to reside there irregularly.14
A Law on Citizenship of the Russian Federation was also introduced in 2002.15 Under Art 13.1, foreign nationals are allowed to apply for citizenship providing they have permanently resided in the Russian Federation for five years since they were granted permanent residence permits. This requirement excludes persons who have resided in Russia irregularly, regardless of the duration, it would therefore exclude citizens of the former Soviet Union who have not obtained permanent residence status in the Russian Federation. Under Art 13.2 persons granted political asylum and refugee status may be able to apply for citizenship after a shorter period.
The Russian Federation acceded to the Geneva Convention in 1993 and the Russian Constitution provides in Art 63.1 that foreign citizens shall be granted political asylum “in conformity with the commonly recognized norms of international law.”16 It also guarantees that people will not be extradited if not classed as criminal by the law of the Russian Federation or if persecuted for their political views or actions.
Art 1 of the Russian Federation Law on Refugees provides for the granting of asylum and refugee status as set out in the 1951 Convention Relating to the Status of Refugees.17 Art 12 of the Russian Federation refugee law is the basis for temporary asylum or complementary protection for persons who have no grounds to be recognized as refugees but cannot be expelled from the Russian Federation for humanitarian reasons. Applicants are legally obliged to asylum at the border but may also apply at regional Ministry of Interior offices.
Citizens from the former Soviet Union may also be granted “forced migrant” status under the Law on Forced Migrants of1995. Art 1 defines forced migrant status.18 A distinction is made between refugees and forced migrants, who were previously granted refugee status, on the basis that “forced migrants” law applies primarily to citizens of the Russian Federation or citizens of the former Soviet Union who are forced to leave their homes because of violence, persecution or fear of persecution, whereas the refugee law applies to non-citizens of the Russian Federation.
Background of General Equilibrium Models
General equilibrium, a concept which dates back to Leon Walras (1834-1910), is a pillar of modern economic thought. General equilibrium recognizes that there are many markets in an econo-
14 See: A. Niaz, “Russian Federation: Immigration Law and Policy,” Legislationline, May 2005, available at [http:// www.legislationline.org].
15 Federal Law No. 62-FZ of 31 May, 2002 on Russian Federation Citizenship (with the Amendments and Additions of 11 November, 2003; 2 November, 2004).
16 Art 63.1 of the Constitution of the Russian Federation, Adopted on 25 December, 1993 (with amendments of 1 September, 1996; 2 October, 1996; and 6 September, 2001).
17 Federal Law of the Russian Federation No. 4528-1 of 19 February, 1993 on Refugees (with the Amendments and Additions of 28 June, 1997; 21 July, 1998; 7 August, 7 November, 2000; 30 June, 2003; and 29 June, 22 August, 2004).
18 The Law of the Russian Federation on the Forced Migrants, 1995 (with the Amendments and Additions of 7 August, 2000; 24 December, 2002; and 23 December, 2003).
my, and that these markets all interact in complex ways with each other. In rough terms, everything depends on everything else. Demand for any one good depends on the prices of all other goods and on income. Income, in turn, depends on wages, profits, and rents, which depend on technology, factor supplies and production, the last of which, in its turn, depends on sales (i.e., demand). Prices depend on wages and profits and vice versa.
Computable General Equilibrium (CGE) modeling specifies all economic relationships in mathematical terms and puts them together in a form that allows the model to predict the change in variables such as prices, output and economic welfare resulting from a change in economic policies. To do this, the model requires information about technology (the inputs required to produce a unit of output), policies and consumer preferences. The key of the model is “market clearing,” the condition that says supply should equal demand in every market. The solution, or “equilibrium,” is that set of prices where supply equals demand in every market— goods, factors, foreign exchange, and everything else.19
Figure 5
S o u r c e: Created by the author.
19 See: T. Hertel, R. Keeney, M. Ivanic, L.A. Winters, “Distributional Effects of WTO Agricultural Reforms in Rich and Poor Countries,” Economic Policy, April 2007, pp. 289-337.
THE CAUCASUS & GLOBALIZATION
As presented in Fig. 5, a CGE model is a closed system. This means that no production or financial flow escapes the system and none are created outside of the system. In basic closure terms, we assume output will equal income. Households, businesses, the government, and the financial sector, and the foreign sector are all connected by real flows and financial flows. Intuitively, the idea of a “general” equilibrium is captured; any given market is connected to all of the other markets for the system.
Over the last 25 years, CGE models have become an important tool for analyzing economic issues, including trade policy, taxation policy, technological growth, energy policy, environmental issues, and even warfare. This development is explained by the ability of CGE models to provide an elaborate and realistic representation of the economy, including the linkages between all agents, sectors and other economies. While this complete coverage permits a unique insight into the effects of changes in the economic environment throughout the whole economy, single country, and especially global CGE models very often include an enormous number of variables, parameters and equations.20
CGE modeling is a very powerful tool, allowing economists to explore numerically a huge range of issues on which econometric estimation would be impossible; in particular to forecast the effects of future policy changes. The models have their limitations, however. First, CGE simulations are not unconditional predictions but rather “thought experiments” about what the world would be like if the policy change had been operative in the assumed circumstances and year. The real world will doubtless have changed by the time we get there. Second, while CGE models are quantitative, they are not empirical in the sense of econometric modeling: they are basically theoretical, with limited possibilities for rigorous testing against experience. Third, conclusions about trade and other policies are very sensitive to data assumption. One can readily do sensitivity analysis on the parameter values assumed for economic behavior, although less so on the data, because altering one element of the base data requires compensating changes elsewhere in order to keep the national accounts and social accounting matrix in balance. Of course, many of these criticisms apply to other types of economic modeling, and therefore, while imperfect, CGE models remain the preferred tool for analysis of many global issues.
The Global Trade Analysis Project
One of the most widely-used CGE models is the GTAP Model. The Global Trade Analysis Project (GTAP), with headquarters at Purdue University, has organized a consortium of national and international agencies which provide guidance and base-level support for the Project.21
GTAP is a multi-regional CGE model which captures world economic activity in 57 different industries of 66 regions. The underlying equation system of GTAP includes two different kinds of equations. One part covers the accounting relationships which ensure that receipts and expenditures of every agent in the economy are balanced. The other part of the equation system consists of behavioral equations which based upon microeconomic theory. These equations specify the behavior of optimizing agents in the economy, such as demand functions.22 Input-out tables summarize the linkages between all industries and agents.
20 See: M. Brockmeir, “A Graphical Exposition of the GTAP Model,” GTAP Technical Paper, No. 8, October 1996, Minor Edits, January 2000, Revised, March 2001.
21 See: Global Trade Analysis Project (GTAP), Department of Agricultural Economics, Purdue University, available at [https://www.gtap.agecon.purdue.edu/about/consortium.asp].
22 See: M. Brockmeir, op. cit.
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The mathematical relationships assumed in the GTAP model are simplified, though they adhere to the principle of “many markets.” The simplification is that thousands of markets are “aggregated” into groups. For example, “transport and communications services” appear as a single industry. In principle, all the relationships in a model could be estimated from detailed data on the economy over many years. In practice, however, their number and parameterization generally outweigh the data available. In the GTAP model, only the most important relationships have been econometrically estimated. These include the international trade elasticities and the agricultural factor supply and demand elasticities. The remaining economic relationships are based on literature reviews.
The Model Employed for Post-Soviet Migration to Russia
The model employed in this paper is that of the GTAP project. While the core database has 57 sectors and 66 regions, I have aggregated the matrices to simplify the world into just three regions: Russia, the rest of the former Soviet Union, and the rest of the world. I have also aggregated the sectoral data into six sectors: food, manufacturing, services, minerals and metals, energy, and other natural resources. Data for factors of production are disaggregated into land, unskilled labor, skilled labor, capital, and natural resources.
The data is first “calibrated,” meaning the model is solved for its original equilibrium prices and volumes in all markets. This baseline is meant to represent the economy as is, before any shock takes place. After this, a “shock” is introduced. The shock is the movement of millions of potential workers to the Russian Federation from all of the other former Soviet republics. While U.N. data shows these migration flows are not evenly distributed among the different states, the GTAP database treats the republics other than Russia as one body. Separate social accounting matrices are not yet available for each of the former Soviet republics. So the experiment will not distinguish between, for example, migrants to Russia from Uzbekistan and migrants from Tajikistan.
This paper makes two experiments. The first is based on U.N. data. Based on U.N. migration data, approximately 1.07 million people moved to Russia from these other states. The shock to the CGE model is two-fold; a 1.07 increase in the labor force in Russia accompanied by a 1.07 decrease in the labor force in the other republics. The question is then, what will this “shock” do to the destination and source economies.
The second experiment is the same as the first, but assumes a movement of 5 million people. Such an experiment seemed appropriate for two reasons. First, the U.N. data seems like a major underestimation of the true flow of workers into Russia. The Russian government’s restrictions on registration and residency permits (propiska) likely mean the true number of migrants in Russia is much higher. A second reason to consider the larger migration number is sensitivity analysis. As the results will show, the large migration of workers doesn’t seem to have a large effect on national output. Pushing the model with a larger shock is way to test the results for “robustness.” If the direction of the results is the same for big shocks as for small shocks, the modeler can feel more comfortable in the findings.
Model Results
In general, the macroeconomic impact of migration into Russia appears surprisingly small. The magnitude of the results does not appear to significantly depend on the size of the shock, i.e. the size
of net migration into Russia. U.N. data suggests that 1.1 million people moved to Russia in the years following the Soviet breakup. But even if a liberal estimate of 5 million migrants is assumed, the macro effects are small.
Real GDP is unaffected in both the source and destination countries. According to the model results, the net inflow of 1.1 million migrants into Russia caused a mere $27.2 million increase in Russia’s real GDP. Such a small increase in production is negligible. The same is true in the other former Soviet republics and for the world as a whole (see Table 1).
Table 1
Change in Real GDP (millions of dollars)
Region % Change GDP GDP Before Shock GDP After Shock Change in GDP
Russia 0.01 309,947.94 309,975.16 27.22
Rest of U.S.S.R. 0.00 104,328.18 104,326.76 -1.42
Rest of World 0.00 30,864,324.00 30,864,324.00 0.00
S o u r c e: Results of CGE Model.
Overall welfare in all regions is barely affected as well. Equivalent variation is a measurement designed to capture the overall welfare effect of a shock on both producers and consumers in an economy. As presented in Table 2, equivalent variation measures closely follow the small GDP changes.
Table 2
Welfare Effect as Measured by Equivalent Variation (millions of dollars)
Region Equivalent Variation
Russia 26.25
Rest of U.S.S.R. -1.13
Rest of World 0.14
S o u r c e: Results of CGE Model.
Welfare effects can be decomposed into major contributing factors. This decomposition is presented in Table 3. In Russia, the population effect measures $2.7 billion, but this is cancelled out by negative allocation efficiency effects (-$1.0 billion) and endowment effects (-$1.6 billion). Essentially, this means that the migrants coming to Russia gain themselves in the form of higher incomes than they would have earned in their source countries. But Russia as a whole is not much better off for two reasons. First, factor incomes for the existing labor force decrease. And second, with more people but equal production, the allocation of output becomes less efficient. While these effects present themselves, it is again worth noting that the magnitude of the changes is very small in relation to the size of the Russian economy.
Welfare Decomposition (millions of dollars) Table 3
Region Alloca- tive Effi- ciency Endow- ment Popula- tion Terms of Trade Investment- Savings Total
Russia -995.6 -1,648.4 2,671.3 -1.9 0.9 26.2
Rest of U.S.S.R. 186.0 737.6 -925.0 0.3 -0.0 -1.1
Rest of World -0.5 0.0 0.0 1.6 -0.9 0.1
TOTAL -810.2 -910.9 1,746.3 0.0 0.0 25.3
S o u r c e: Results of CGE Model.
The rest of the former Soviet Union experiences much of the opposite. A negative population effect simply reflects the fact that fewer people are present to earn incomes. But this negative effect is offset by positive effects for efficiency and to factor endowments. In other words, it appears that those who remain in the other Soviet states experience a rise in factor payments and the allocation of goods is improved as the existing output is allocated among a smaller group of consumers.
There are small (basically negligent) changes in output across sectors (see Table 4). While no sector in any region experiences a significant change, the largest increases in production occurs in Russian food. This is likely a signal that a larger population simply needs to eat more than a smaller one. Likewise, the rest of the U.S.S.R. region produces slightly less food, though not an equal change.
Table 4
Percent Change in Sector Output
Sector Russia Rest of U.S.S.R. Rest of World
Food 0.10 - 0.03 0.00
Manufacturing 0.01 0.00 0.00
Services -0.02 0.01 0.00
Minerals and Metals 0.01 0.00 0.00
Energy 0.00 0.03 0.00
Other Natural Resources 0.02 0.02 0.00
Capital Goods -0.01 0.01 0.00
S o u r c e: Results of CGE Model.
Real incomes (or factor payments) to the various inputs in the economy also change very slightly. In Russia, factors which seem to gain are landowners and capital owners, while factor payments to existing workers fall slightly, both for skilled and unskilled labor. In the other former Soviet republics, both landowners and owners of natural resources lose in real factor payments. Again the effects are nearly negligible (see Table 5).
Table 5
Percent Change in Real Factor Incomes
Sector Russia Rest of U.S.S.R. Rest of World
Land 0.18 -0.05 0.00
Unskilled Labor -0.00 -0.00 0.00
Skilled Labor -0.02 0.01 -0.00
Capital 0.01 0.01 -0.00
Natural Resources 0.00 0.04 -0.00
S o u r c e: Results of CGE Model
Finally, it is interesting to note the changes in international trade of goods caused by this flow of migrants to Russia (see Table 6). According to the model, the flow of migrants causes Russia to import significantly more food—some from the other Soviet republics, but most from the rest of the world. Russia’s net exports of services and energy increase. For the rest of the former Soviet Union, net exports of food increase while the trade balance deteriorates in ever other sector.
Table 6
Change in Trade Balances by Sector (millions of dollars)
Sector Russia Rest of U.S.S.R. Rest of World
Food -20.24 6.84 12.32
Manufacturing 0.30 -1.76 1.15
Services 10.87 -1.14 -8.06
Minerals and Metals 3.69 -0.99 -2.75
Energy 12.01 -4.37 -7.87
Other Natural Resources -0.49 -0.04 0.52
1 S o u r c e: Results of CGE Model |
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Model Limitations and Future Research
Beyond the normal limitations of CGE modeling in general, this experiment has at least two areas in which improvement could be made in future research. First, the migration shock does not include remittances. As with most migrant flows, the people moving from the former Soviet Republics into Russia are sending large amounts of money to relatives and others back in their original countries. This flow of money could be modeled as a net unilateral transfer paid by Russians to the other republics. It would be expected that incomes and consumption levels in the source countries would increase while Russia might experience a decrease.
A second front for further research would be the distinction between the migration of skilled workers and unskilled workers. While consumption patterns might not be expected to change drastically, regional output could be affected. In other words, if more unskilled workers come to Russia, production of agricultural or other labor intensive goods might be expected to experience a larger increase than production of other goods. Likewise, more skilled labor in Russia could tilt more production in favor of goods requiring the employment of skilled labor. These model improvements are left to a future date.
C o n c l u s i o n s
The results of this limited experiment suggest that labor flows are important, but possibly less important to the Russian economy than many might believe. Demographers, social scientists, the Russian Duma, and even ex-President Vladimir Putin (now the prime minister) himself have suggested the Russian labor market is facing a shortage of workers which might be satisfied by labor migration. While this might be true, this CGE model suggests that the macroeconomics as a whole is not very dependent on the inflow of workers from the former Soviet Union (or elsewhere for that matter).
Having said this, however, it is probably important to remember the “static” nature of this CGE model. It asks a counter-factual question: what would have happened if these people had not migrated between regions? The answer takes the existing economic structure as it is and assumes there are more or fewer workers available in particular regions.
What this model is not very good at is capturing the dynamic effects of changes in endowment or economic growth. In many ways, this is a short-run effect versus a long run effect of migration. In the short run, the above results are probably more valid. But in the long run, an economy will absorb the skills, talents, and international relationships of migrant peoples. The economy will likely grow in different ways with an accumulation of different types of capital. This is not something captured in this model. In the long run, migrant flows might very well be more important to the Russia economy than what this CGE exercise is able to capture.
