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The Effect of Municipal Strategic Planning on Urban Growth in Ukraine
Authors: Denys Nizalov and Olena Nizalova, KEI.
In a downturn, the pressure is especially high on governments to produce sensible and effective development strategies to generate needed jobs and increased earnings. A large number of economic development tools were used in the past by local and national governments around the world, designed to facilitate regional and local economic growth. This brief presents the preliminary results from the evaluation of a program implemented in Ukraine.
Bradshaw and Blakely (1999) distinguish three historical waves of popularity for different tools used in economic development, with reference to the US states’ development policy:
- 1st wave – Incentive-based competition for industrial location, so called smokestack chasing (direct incentives to firms, reimbursement of relocation and infrastructure costs, tax-breaks);
- 2nd wave, from the early 80s – Cost-benefit-based assistance, focusing on internal growth (business incubators, start-up funds, trainings);
- 3rd wave, over the last two decades – Building of a “soft infrastructure” (institutions) conducive to economic growth (strategic planning, marketing, public-private partnerships, financing, regulation, intergovernmental collaboration).
While the effect of the first two waves on various growth outcomes was studied extensively (for reviews, see Bartik 1991; Fisher 1997; Wasylenko 1997; Goss and Phillips 1999; Buss 2001) the effect of the policies representing the third wave is less known. There are several reasons for that. These policies were developed relatively recently, they are hard to measure and compare and are most likely to have a long run effect.
A unique example of a third-wave policy was recently evaluated in Ukraine. The Local Economic Development (LED) Project in Ukraine, started by the USAID in 2004, introduced a process of municipal strategic planning into the practice of local government decision making. This Strategic Planning process involves setting goals and priorities for community economic development and coordination of activities in different areas of community life. It also allows the establishment of partnerships among various stakeholders and interest groups, and the mobilization of public and private resources to facilitate economic development.
Until recently, the effect of municipal strategic planning has been assessed exclusively by case-studies. See for example, the cases of Randstad (Priemus, 1994), Lisbon (Alden and Pires, 1996), London (Newman and Thornley, 1997), Hong Kong (Jessop and Sum, 2000), Guangzhou (Li, Yeung, Seabrooke, 2005; Wu and Zhang, 2007), and Hangzhou (Wu and Zhang, 2007). Although the above mentioned cases describe the planning process and the perceived benefits in great detail, they do not address the question of whether the Strategic Planning causes a higher rate of community economic growth or not. There are several reasons for these limitations. The procedure of planning, beyond general similarities, differs greatly in the implementation details from case to case, which makes any comparisons complicated. Moreover, the decision to start the planning process in those cases is thought to be endogenous since cities that are more likely to benefit from strategic planning are also more likely to get involved in this.
The LED example is much more suitable for evaluation. The implementation of the strategic planning system in the participating cities has been performed using a standardized procedure with the help of LED advisors. With one exception, the implementation took from 4 to 12 months. Also, the selection of the participating cities was done by LED personnel based on clear participation rules. Altogether, the LED activities targeted the same goal in each city – FDI growth and creation of new jobs. Moreover, a relatively large number of communities – 74 cities from all regions of Ukraine – were involved in the project by mid-2008.
Internal reports point to a great success of the project. More than 30 cities had by mid-2008 reported an increase in FDI. Collectively, the partner cities reported $700 million of inflowing investment and an addition of about 12,000 jobs.
The impact of the LED project on the following outcomes was evaluated using more rigorous statistical procedures:
- Number of businesses per capita;
- Fixed capital investment per capita;
- Number of jobs per capita;
- Unemployment rate; and
- FDI per capita.
It was found that the LED project had a positive overall effect on the number of businesses, fixed capital investment, and the number of jobs. In absolute values, the introduction of strategic planning lead to 6 to 12 new jobs per 1,000 of population, 18 to 50 new businesses per 100,000 of population, and 5 to7 million USD of investments in fixed capital per 100,000 (controlling for other factors of influence). However, differences in the project effect among the cities were found. The reasons for these differences in impact include:
- the effect was observed at different points of time after the implementation of planning (1 to 45 month by Dec. 2008);
- the cities had different implementation teams (composed of 6 advisors); and
- the municipalities had different administrative subordination (58 cities and 16 small towns of rayon subordination);
The project effects on the number of businesses, fixed capital investment, number of jobs, and the unemployment rate increased each month. The administrative subordination affects only the effectiveness of investments and job creation: the effect is larger for cities than for rural towns. Team-specific differences are evident on all outcomes. This confirms that the implementation have a significant impact on the success of this intervention.
Finally, the effect of LED was compared to the effect of a similar project implemented in Ukraine by UNDP. Provided that the results presented above are robust, it turns out that the effects of the two projects introducing strategic planning are very similar in magnitude and significance.
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References
- Bartik, T.J., 1991. Who Benefits from State and Local Economic Development Policies? Upjohn Institute for Employment Research: Kalamazoo, MI.
- Buss, T.F., 2001. “The Effect of State Tax Incentives on Economic Growth and Firm Location Decisions: An Overview of the Literature,” Economic Development Quarterly 15(1), 90-105.
- Fisher, R.C., 1997. “The Effect of State and Local Public Services on Economic Development,” New England Economic Review March/April, 53-67.
- Goss, E. and J. Phillips, 1999. “Do Business Tax Incentives Contribute to a Divergence in Economic Growth?” Economic Development Quarterly 13(3), 217-228.
- Wasylenko, M., 1997. “Taxation and Economic Development,” New England Economic Review March/April, 37-52.
Do Economic Sanctions Work?
Analysts have interpreted the recent openings in Myanmar and North Korea as the finally successful result of years of international pressure and economic sanctions. At the same time, debate is hot on the scope for similar measures in Iran, Syria and, closer to us, Belarus and Hungary. Does economics have anything to say on this? What can we learn from the analysis of past experiences?
Presidential Elections in Russia: Massive Vote Fraud Ensures that Legitimacy is in Doubt, but the Policy Direction is not
The March 4th, 2012, elections formally returned Vladimir Putin, the paramount leader of Russia since 1999, to the presidency. Despite Draconian restrictions on entry, financing, campaigning by other candidates, Putin’s dominance of TV, blatant use of state employees and funds to his own advantage, and significant vote fraud, the victory was underwhelming in the end. While the official tally was only 63.6 percent in Putin’s favor, estimates of his vote share by independent observers relying on networks of tens of thousands of volunteers were in the range of 49-57 percent of the turnout; even lower. (If his share was truly below 50 percent, a run-off vote would have to take place between Putin and the runner up) The second major outcome of the elections was the successful attempt by civic society to ensure a fair vote count in Russia’s largest city and capital, Moscow, where Putin’s official vote share (45 percent) on March 4th was the same that United Russia achieved in the December 4th parliamentary elections. (Generally, Putin polls much higher than United Russia.) The third outcome was the emergence of Mikhail Prokhorov, a billionaire with negligible experience in politics, as a major political force representing large cities and young educated voters.
The Success of Civic Society in Moscow and Vote Fraud Elsewhere
The central issue in the wake of the March 4th elections is the extent of fraud organized by the incumbent. Massive fraud during the December 4th parliamentary elections generated mass protests in response. In total, hundreds of thousands of Muscovites took part in four large rallies held during this winter. (No political rallies of comparable size, except for the state-sponsored pro-Putin ones, have taken place during the last 15 years.) A similar discrepancy between the actual vote and official returns was expected to generate even larger protests this time round.
Despite dozens of reported and video-documented cases of organized groups brought in to Moscow to vote multiple times and the presence of tens of thousands of observers, public outrage after massive vote fraud in the parliamentary elections last December is likely to have prevented the most outrageous and blatant forms of fraud during these elections. No less important, it is also likely that they generated less directly observable forms of electoral manipulation. Not surprisingly, for Moscow, the vote count by Citizen Observer, Golos, and other independent and highly respected observer organizations nearly coincided with the official election results, certified by the widely despised Central Election Commission (CEC). (Since December, the name of the head of CEC, Vladimir Churov, has become a synonym for incompetence and of fawning loyalty to the incumbent.) This does not mean, however, that no fraud took place outside the capital.
Figure 1. Cross-plot of the United Russia (Putin) vote share vs. turnout in the December 4, 2011, parliamentary elections and the March 4, 2011, presidential elections in Moscow. (Courtesy of Alexei Zakharov, HSE and Citizen Observer, using the CEC data.)
A side effect of the fair vote count on March 4th, 2012, in Moscow was that it highlighted the extensive centrally-organized fraud in parliamentary elections held on December 4th, 2011. (See the December 2011 issue of the FREE Policy Brief for a snap analysis of the parliamentary elections.) Figure 1 shows that the suspicious-looking relationship between the turnout and the Putin-led United Russia Party, highly visible in December (top figure), completely disappeared in March (bottom figure). Thus, the strong correlation between turnout and the United Russia vote share is a result of ballot-stuffing rather than anything else (theoretically, such a correlation might be caused by some socio-demographic characteristics of United Russia’s supporters). Similarly, Figure 2 exhibits a “normal” (Gaussian) distribution of total votes for United Russia/Putin by turnout (this is what should be expected theoretically, and is consistently observed in democratic elections around the world) on March 4th (bottom figure) and an unusual distribution, a result of changed voting protocols on December 4th (top figure).
Figure 2. Number of ballots by turnout in the December 4, 2011, parliamentary elections, and the March 4, 2011, presidential elections in Moscow. (Courtesy of Maxim Pshenichnikov using the CEC data.) Note the spikes on 70,75,70,85, and 90 percentiles on the left graph, a result of “targeting” by election officials. 
Outside Moscow, the situation was different. Across the country, independent observers documented ballot stuffing and manipulation of local vote returns. St. Petersburg, the second largest city in Russia with a population of just over 4 million and the cradle of the “Putin’s team”, is a case in point. The preliminary estimates, based on a (nearly random for these purposes) sample of 269 polling stations (which is about 12 percent of the total number of station in the city), shows that the actual vote share for Putin was 50 percent rather than the officially reported 65 percent, while for Prokhorov it was 22 percent instead of 14 percent, and for Zyuganov 15 percent instead of 11 percent in the official tally. These estimates are based on the comparison between the official results as certified by the Central Electoral Commission with official copies of vote protocols signed by accredited observers and members of local electoral commissions at the polling stations. In other words, the discrepancy is a result of vote fraud at the level of the territorial electoral commission instead of more conventional forms of fraud, such ballot-stuffing at polling stations.
New Faces of Russian Politics
Three of the four competitors against Putin on March 4th were veterans of Russian politics. The Communist party Chairman, Gennady Zyuganov, lost presidential elections to Boris Yeltsin in 1996, Putin himself in 2000, and to Dmitry Medvedev, Putin’s figurehead “heir,” in 2008. (In 2004, the communists ran a minor candidate). Vladimir Zhirinovsky, a perennial nationalist candidate for presidency since 1991, has maintained a parliamentary faction for his one-man party for 20 years, but has never come close to winning the presidency. Sergei Mironov, a former Putin ally (in 2004 he ran for presidency with the announced goal “to help Putin win presidency”), was the main beneficiary of the December 4th, 2011, vote when many people supported his party primarily for the reason that parties they would have otherwise voted for were banned from participation. By official tally, Zyuganov got 17.2 percent (2nd place), Zhirinovsky 6.2 percent (4th place), and Mironov 3.9 percent (5th place). Despite the fact that these three have been on the ballot for a long time, they have never succeeded in presenting a genuine alternative choice for Russian voters at the polls and therefore posed no serious threat to Putin’s authority.
Mikhail Prokhorov, the 2nd richest person in Russia according to Forbes, ran a campaign that was watched warily by both Putin in Kremlin and Putin’s opponents in the liberal camp, and came in 3rd place with an official total of 8.0 percent. In Moscow, his result was even more impressive with 22 percent of the vote, second only to Putin’s 45 percent. While Prokhorov certainly benefited from the absence of Grigory Yavlinsky, who failed to clear the (unheard of in democratic countries) requirement to collect 2 000 000 signatures, and other liberal politicians, his results exceeded the previous combined returns of the liberal parties and candidates in parliamentary and presidential elections in 2000. The success of his candidacy have raised doubts on a long-held assumption in Russian politics that a rich, not to mention very rich, candidate has no chance of gaining traction in popular vote.
Another new face in Russian politics, Alexei Navalny has a law degree, business background, and was a member of the leadership in the Yabloko party (expelled in 2007) before becoming a famous blogger and shareholder activist in the beginning of 2010. His blog (navalny.livejournal.com) is now one of the most popular blogs in Russia, with more than 66,000 followers. A major boost to its popularity was the “Rospil” project that focused on protecting minority shareholders of large state-owned companies (and, by extent, on the management of the taxpayers’ property by the Putin government). Navalny used his blog to organize large-scale petitioning and litigation campaigns related to corruption in state-controlled companies. As a result of these activities, Navalny was described by the BBC in 2011 as “arguably the only major opposition figure to emerge in Russia in the past five years.” (Obviously the BBC has not foreseen the rise of Prokhorov.) After December 4th, 2011, Navalny became a major leader of the protests and organizers of election observers.
“Staying the Course”
President-elect Vladimir Putin will start his new 6-year term in difficult times. The election raised questions about his true legitimate level of popular support, yet there is little doubt that he does not face any viable alternative challengers in the near future. Given that Putin has proven himself extremely rigid in the choice of policy and personnel (he would not get rid of close subordinates even if wide-spread corruption allegation would make them a visible drag on his popularity), the new government is not expected to be radically different from the current one (which features most of the ministers serving for 5-10 years in their current capacity). His anointed prime-minister is not a new face either. Dmitry Medvedev, who served as Russia’s president for the last 4 years, is not expected to bring forward any major policy changes.
Fortunately for Putin the opposition is not organized and cannot settle on any particular message or alternative policy direction, let alone viable leader. The protest movement during the winter of 2011-12 was characterized more by decentralized leadership, featuring a number of prominent literature, arts, and entertainment figures. With its goal to ensure fair elections, it has, however, united a very diverse group of smaller movements ranging from radical young communists to libertarians despite its not having provided an alternative leader to Putin. In the end, the outcome of the March 2, 2012, presidential election has ended the myth of a significant Putin majority, casted considerable doubt on his legitimacy and has shown that Russians seem hungry for a change. It has, however, also left a big question mark on what the opposition’s next steps are and who the alternative could be.
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Inflation Expectations and Probable Trap for Macro Stabilization
As of today, a majority of the negative consequences of the deep Belarusian currency crisis of 2011 seem to have been realized. Hence, the Belarusian economy is now ‘purified’ from main macroeconomic distortions and has a chance for sustainable long-term growth. Nevertheless, there are signals that some nominal and real inertia may generate new shocks for the national economy. From this view, the money market is of great concern, while interest rates signal maintained high inflation expectations. High and unstable expectations may entrap monetary policy and generate new shocks for the Belarusian economy. In this policy brief, we deal with a visualization of inflation expectations and argue for the necessity of a new nominal anchor in order to stabilize expectations for future periods.
In 2011, Belarus experienced its highest inflation and devaluation in modern history. These were consequences of the automatic macroeconomic adjustment determined by a number of both long- and short-term distortions in the national economy. Changes in prices and exchange rate adjusted real parameters towards their long-run equilibrium level. Hence, from a long-run perspective, one may interpret these adjustments as favorable since they ‘purified’ the economy from the macroeconomic imbalances that may have hampered growth. Furthermore, shifting from exchange-rate (XR) targeting to a managed float is another essential aftermath of the currency crisis. Economic authorities had to recognize that accommodative monetary policy (MP) was not compassable with XR targeting since it resulted in a considerable overvaluation of the real XR, and correspondingly, an incredibly large current account deficit. Thus, the new exchange rate regime may be argued to be a new automatic stabilizer for Belarus, providing the level of current account balance consistent with other macroeconomic fundamentals. Overall, the current stance of the national economy might be treated as a chance to “begin again from the ground up”. In this sense, the Belarusian economy as of today is sometimes compared to the Russian economy after its crisis in 1998, which then performed particularly high growth rates.
In our opinion, realizing the opportunity for a strengthening of long-term growth through structural changes undoubtedly should become a policy priority of Belarus in the near future. However, it should be emphasized that despite “purification” from major macroeconomic imbalances, there are still a long list of short-term challenges. In particular, one may stress the risks of expansionary policy revival; increasing external debt burden; growth in non-performing loans, which may undermine the solvency of the banking system; reduction of foreign demand due to shocks in global economy. These risks are more or less observable and may be monitored. Hence, the realization of one or the other shocks from this list might not come as a surprise, and economic authorities seem to at least realize this, and when possible, take prevention measures.
At the same time, another challenge seems to be more adverse and urgent; namely, the question of inflation and devaluation expectations. In economic theory, expectations play a crucial role in affecting behavior of economic agents. Recognition of the role of expectations at the money market determined intention to “subject” and stabilize these within modern monetary policy frameworks.
In Belarus, given the recent history of high inflation and devaluation, corresponding expectations of Belarusian economic agents are likely to be rather high. Moreover, shifting from XR targeting to a managed float has not yet resulted in provision of a new nominal anchor for the public.
For instance, disinflation was declared to be a priority goal, but there are no strict commitments on its numerical value, as well as in respect to procedures and mechanisms to provide disinflation trends. As of today, the Belarusian MP regime can hardly be classified as a standard regime. The MP Guidelines for 2012 assume indicative targets on international reserves, refinancing rate and the growth rate of banks’ claims on the economy. The latter witnesses the propensity to monetary targeting. However, the instable relationship between the monetary aggregate to be targeted and the ultimate goal (inflation), as well as the indicative nature of this commitment give rise to doubts in respect to treating it as monetary targeting. Furthermore, commitment on bank claims on the economy can hardly be treated as a nominal anchor for the public. According to the taxonomy of MP regimes by Stone (2004), Belarus is currently closer to the weak anchor regime, which assumes “no operative nominal anchor…and central bank reports a low degree of commitment… and high degree of discretion”.
Thus, our hypothesis assumes that there has been an adverse shock in inflation expectations due to weak nominal anchor and recent experience of huge inflation. If that is the case, this may be an additional source of shock for the money market, which may cause a new wave of macroeconomic instability. In order to make policy recommendations, this hypothesis needs empirical support. However, it is difficult to identify expectations in empirical analyses since this variable is typically unobservable and cannot be univocally measured. Instead, expectations are most often treated indirectly through other variables. Many central banks deal with the results of sociological polls on this issue, but these approaches may suffer from different economic meanings and measurements of inflation expectations by economic agents.
An alternative approach was proposed by St-Amant (1996) and extended by Gotschalk (2001), who base on famous Fischer equation representing current nominal interest rate as the sum of ex-ante real interest rate and expected inflation. Further, based on the approach by Blanchard and Quah (1989), structural vector autoregression (SVAR) between nominal and real interest rate is identified with a number of restrictions, which allows decomposing changes in the nominal rate to those associated with ex ante real rate and inflation expectations. The latter may be used as a measure of inflation expectations. Such a measure of inflation expectations assumes explicit economic meaning referring to the money market, i.e. the rate of future inflation, which will provide the, by economic agents, expected level of interest rate. Taking the data from statistics (not polls) and international comparability of such estimates are important advantages of this approach.
We applied this methodology to Belarusian data (nominal and real interest rate on ruble households’ deposits with a term more than a year). The obtained time series measure changes in inflation expectations in the current period for a period of the next 12 months. However, our goal is to visualize the level of inflation expectation and not changes in expectation. Therefore, we use the series in levels, choosing January 2003 as the base period (when National Bank of Belarus actually shifted to XR targeting regime), and assigned a zero level (as starting one) to it. The obtained series of inflation expectations is provided in Figure 1.
Figure 1. Inflation Expectations in Belarus
The estimated series of inflation expectations show a decrease in 2003 – mid 2005, which may be explained by the effectiveness of the new nominal anchor (XR), and correspondingly the expected disinflation. The expectation of reflation in late 2005 till late 2007 may be explained by the more expansionary policy and changes in Russian preferences that took place during this period. After that, there was a period of stable expectation, which is likely to be explained by the credibility of the nominal anchor (nevertheless, there was a shock in late 2008 that is associated with the impact of the global crisis).
The most considerable shock took place in the beginning of 2010, which has a lack of intuitive explanation and might be associated with a phase of radically expansionary policy.
Finally, a new significant shock took place in late 2010 – beginning 2011 which might be associated with the visualized problems at the currency market at that time.
Currently, there is a very high level of inflation expectations and its increased volatility in the second half of 2011 seem to be of a great importance. It signals that economic agents do not treat price shocks as a single-shot, but mostly tend to consider it as a long-lasting process. Hence, the absence of a nominal anchor and the fresh memory of huge inflation seem to be responsible for the current high and instable inflation expectations.
Maintenance of high inflation expectations is a dangerous threat for the money market. Propagating inflation through expectations may be considered as a separate channel within the monetary transmission mechanism (along with interest rate, exchange rate and bank-lending channels). In other words, even without additional fundamental preconditions for inflation, inflation expectations may become a self-fulfilling prophecy.
However, during the last two months (December 2011 and January 2012) this adverse effect seems to have been suppressed by monetary authorities, as the monthly inflation rate reduced radically in comparison to average rate in May-November 2011. This is likely to be the outcome of the significant monetary policy tightening that has resulted in a sharp increase in nominal interest rates by banks. On the one hand, such nominal interest rate complies with the shocks in inflation expectations and real ex ante interest rate (the latter grew as well at the background of the crisis). In other words, current level of nominal interest rates will equalize ex post real rate with ex ante real rate if the actual inflation rate has been as high as current inflation expectations. But on the other hand, if actual inflation had been much lower than expected one (and it tends to be so, in case of keeping on conservative MP), ex post real rate would be much higher than the ex-ante one. For instance, such a situation has already been peculiar during December and January: according to our estimations, ex ante real interest rate in December was about 3.6% in annual terms (preliminary data on January shows that it in this month it is rather similar), but annualized ex post real rate for these months is about 30%.
This suggests that there is a trap for the monetary authorities. If they keep high interest rates, based on the expected inflation, the impact of expectations on actual inflation will be mitigated, but the losses, say in terms of output, will be high because of the extremely high ex post real interest rates. If the monetary authorities facilitated the rapid reduction of nominal interest rates, current nominal rates would not guarantee ex ante real interest taking into consideration the high inflation expectations, which would then constitute a severe shock for the money market. Hence, the mechanism of self-fulfilling prophecy would work.
Furthermore, the increased ex ante real rate (and high probability of even higher ex post real rate in national currency) could give speculative incentives for a number of economic agents. For example, many agents could increase the share of national currency in their savings portfolio, either avoiding buying hard currency (which took place during the peak of the currency crisis) for new deposits, or changing the nomination of their deposits to the national currency (i.e. selling the hard one). In a sense, this trend may be interpreted as the compensation of losses on ruble deposits in the last year, which is needed to revive the demand for such deposits. But in any case, these internal processes (along with restricting money supply by the National bank) influence the domestic currency market. Through this, the supply and demand are formed not only due to current and financial international flows. Hence, due to these incentives for hard currency supply and demand, the current value of the nominal rate may substantially deviate from the equilibrium rate. The latter may be defined as in Kruk (2011): the one that may clear the market immediately (given short-term trends in current account flows at the background of medium-term values of other fundamentals).
Figure 2. Actual and Equilibrium Exchange Rate
Note: For 2010Q1-2011Q1 official rate of the National bank is taken as actual nominal rate, for 2011Q2 the exchange rate at the ‘black market’ (used by internet shops), and for 2011Q3 ‘black market’ and later the exchange rate of the additional BCSE session are taken.
The assessments of the equilibrium exchange rate based on this methodology (Kruk (2011)) show that in the third quarter, the actual rate almost equals the equilibrium rate. For 2011Q4, all necessary data is not available yet, but an approximate assessment correction of the equilibrium rate of the Q3 for average inflation between Q3 and Q4 may be used (i.e. in real terms the rate should not have changed in order to sustain equilibrium). Such an assessment indicates that the actual rate in the Q4 is again overestimated by roughly 5-10% in comparison to the equilibrium rate.
At a first look, such an ‘overhang’ at the domestic currency market seems to not be a great problem. But along with the trap stemmed from the high and unstable inflation, this may contribute and propagate possible shock at the money market. Furthermore, this ‘overhang’ is due to speculative incentives, which in turn, are due to high inflation expectations. Hence, high and unstable inflation expectations are a prime cause of this ‘overhang’.
Finally, we may argue that unfavorable inflation expectations is a multidimensional problem, which generates grounds for shocks at the money market and entraps monetary policy at the current stage. Therefore, restraining inflation expectations must currently be an absolute and unconditional priority of economic policy.
This gives rise to the issue of which policy tools that are needed for solving this problem. Tight monetary policy alone may not be enough and/or its losses in terms of output may be unacceptably high, especially taking into account that keeping the Belarusian economy depressed is likely to cause huge migration and thus reducing the prospects for long-term growth.
Our view on the problem of inflation expectations supposes that they stem both from recent experience of very high inflation and the absence of nominal anchor. Inflation memory cannot easily be removed, but introducing a new nominal anchor seems to be worthwhile. Among possible options, given the desire to preserve autonomous monetary policy in Belarus, the introduction of inflation targeting (IT) is seen as inevitable. A shift to this regime is associated with plenty of obstacles and might not be realized immediately (Kruk (2008)). A gradual shift to IT through its intermediary phases (so called IT Lite) is more expedient and complies more with the requirement of obtaining new powers and capacities at the National Bank of Belarus.
Taking on more and more strict commitments in terms of inflation and implementing mechanisms and procedures peculiar for IT (the latter is even more important than commitments themselves) will increase credibility and public trust for the National bank. The other side of the coin involves decreasing and less volatile inflation expectations, which do not challenge monetary policy and facilitate low and stable inflation. Another advantage of IT is the possibility to mitigate price shocks.
Our main policy recommendation is therefore that it is necessary to shift to an IT framework as soon as possible, starting from exploiting the forms of IT Lite. The advantages of this step overweigh all the obstacles, including those associated with the reluctance of economic authorities to change institutional preconditions.
However, one important clause should be emphasized. Shifting to IT (especially gradually through IT Lite) does not guarantee that current high inflation expectations will be reduced automatically and immediately. In other words, it does not guarantee that the cost of reducing inflation in terms of output will decrease (though for the present Belarusian situation there are grounds to suspect that it would facilitate). For instance, Mishkin (2001) shows that “there appears to have been little, if any reduction, in the output loss associated with disinflation, the sacrifice ratio, among countries adopting inflation targeting… The only way to achieve disinflation is the hard way: by inducing short-run losses in output and employment in order to achieve the longer-run economic benefits of price stability”. However, an introduction of IT assumes that new shocks in inflation expectations may be prevented, and due to it, low and stable inflation will be more likely.
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References
- Blanchard, O., Quah, D. (1989). The Dynamic Effects of Aggregate Demand and Supply Disturbances, American Economic Review, Vol. 79, No.4, pp.655-673.
- St-Amant, P. (1996). Decomposing US Nominal Interest Rate into Expected Inflation and Ex Ante Real Interest Rates Using Structural VAR Methodology, Bank of Canada, Working Paper No. 96-2.
- Gottschalk, J. (2001). Measuring Expected Inflation and the Ex Ante Real Interest Rate in the Euro Area Using Structural Vector Autoregressions, Kiek Institute of World Economics, Working Paper No.1067.
- Mishkin, F. (2001). From Monetary Targeting to Inflation Targeting: Lessons from Industrialized Countries, World Bank, Policy Research Working Paper No. 2684.
- Kruk, D. (2008). Optimal Instruments of Monetary Policy under the Regime of Inflation Targeting in Belarus, National Bank of Belarus, Materials of International Conference “Efficient Monetary Policy Options in Transition Economy”, pp. 305-322.
- Kruk, D. (2011). The Mechanism of Adjustment to Changes in Exchange Rate in Belarus and its Implications for Monetary Policy, Belarusian Economic Research and Outreach Center, Policy Paper No. 004.
Is Regional Policy Effective in the Long Run? Learning from Soviet History
Regional inequality has been a pressing issue in many countries, and also between the countries of the European Union. Unequal economic development, where some regions develop successfully and prosper while other regions stagnate, is often viewed as a source of social instability and economic inefficiency. Many kinds of regional policy have been proposed in order to mitigate such a situation by promoting growth in lagging regions. The policies range from subsidies and favorable tax policies for business investment to large-scale government investment projects. The ultimate goal of all regional policies is to create an environment for sustainable growth in regions that have fallen behind. In theory it might appear that a policy, which is implemented during a specific period of time, would be sufficient to achieve sustainable development: subsidies or creation of infrastructure would lure firms into a region and create a favorable environment for economic agents (both firms and people). The temporary policy would create agglomeration externalities that would ensure sustainable development even after the policy is discontinued.
However, are such regional policies in fact successful? Researchers often observe a short-run impact, but it is less clear whether regional policy can make a difference in the long run. From the literature on historical “natural experiments”, we know that spatial structures of economic activity are very resilient to temporary impact. For example, the wholesale destruction and loss of life in WWII seems to have had little or no effect on the regional shares of population and manufacturing in the long run. On the other hand, significant and permanent (or long-lasting) changes to market access, such as the division ofGermanyafter WWII, do reshape the spatial economy in the long run.
Our study looks at the long-run patterns of Soviet city growth in light of Stalin’s industrialization and WWII. The Soviet government’s investment decisions during that period were dictated to a large extent by military strategy and ideology. Massive relocation of productive resources from west to east before, during, and after WWII represents a unique natural experiment, in which production factors were destroyed in some parts of the USSR, while new production facilities and infrastructure were created in other regions of the country. Using a unique dataset, we test whether Gulag camps, wartime evacuation of industry, and location near the war front had a long-run effect on city size.
In the 1930s-1950s, Stalin’s system of penal labor camps (the Gulag) was widely used as a source of cheap labor, especially in remote locations where there was no other available labor force. Penal labor was used in a variety of sectors (logging, mining, manufacturing and construction). Presence of a camp near a city or town usually meant that this location was chosen by the Soviet government for an investment project. We trace the impact of having a camp nearby on city growth from 1930 to the present day.
Evacuation of enterprises from western to eastern regions of the USSR (to avoid their possible capture by the advancing German army) is traditionally named among factors that determined post-war growth of cities in the Urals andSiberia. Indeed, data show that the majority of evacuated enterprises never returned to their original location in the westernUSSR. Western cities that sent enterprises into evacuation often lost their significance in the immediate post-war period. We test whether evacuation affected the growth of cities in the longer run, ceteris paribus.
Unfortunately, no detailed data on deaths and destruction in Soviet cities during WWII are publicly available. We therefore measure the impact of wartime damage by constructing a set of indicators for cities that were occupied or were close to the front line during WWII.
The results show that (controlling for pre-war city size, rate of growth, and geographical location) occupation and location 30 km or 200 km from the front line do have a negative and statistically significant effect on city size by 1959. However, this effect disappears by 1970. This is consistent with findings forJapanandWestern Germany, where pre-war trajectories of city growth were restored after 25-30 years.
Surprisingly, the result is roughly the same for cities which hosted evacuated enterprises. Controlling for pre-war size and growth rate, geography and presence of Gulag camps, cities that received evacuated plants grow faster until 1959, but the difference is not statistically significant in 1970 and later. Thus, contrary to the commonly held belief, the effect of evacuation was only temporary.
By contrast, the presence of a Gulag camp increases city size in a long time horizon. Gulag cities grow faster not only in the 1930s-1950s when the Gulag system was operational, but also in the 1970s and 1980s. On average, the Gulag effect only disappears in the 1989 population census.
Specialization of the camp also makes a difference. Effect on city population from a camp where prisoners were involved in agriculture or logging is short-lived. Such camps were not used to build capital or infrastructure, so the nearby cities did not become more attractive for free labour. However, if a city had a camp where prisoners worked in manufacturing, mining, or construction of production facilities or housing, its population increased permanently. Compared with the best match from a control group (a city of similar characteristics, but without a Gulag camp), such a city accrued 50% more population, and this difference remains statistically significant even until the census of 2010.
Overall, the evidence on Soviet city growth supports the common finding: the direct effects of WWII were relatively short-lived. The experience of enterprise evacuation shows that one-shot relocation of production factors by the state also fails to produce robust changes in the geographical redistribution of economic activity in the long run. However, when the Soviet government established new industrial centers in the eastern parts of theUSSR, and made massive investments in production facilities and infrastructure using Gulag labor, it managed to permanently shift the geography of economic activity. This example illustrates the size and scope of impact that is required to affect economic geography in the long run.
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Who Needs a Safety Net?
One definition of safety net found on the internet is the following: “a net placed to catch an acrobat or similar performer in case of a fall”. This brings to my mind the thrilling performances I saw at the circus when I was a child and I have to admit in most cases there was a safety net. Only in some rare occasions it was removed and the increased tension became palpable. We knew that only the best acrobats could dare performing in those conditions since the slightest mistake or distraction could lead to disastrous consequences. Born in this context, the term safety net has soon been extended beyond circuses. The same internet source, right below the standard definition adds: “fig. a safeguard against possible hardship or adversity: a safety net for workers who lose their jobs”.
Imagine you are a European worker in a time of crisis. You are the only breadwinner in your family and you become unemployed. The situation of your family is going to worsen significantly, but you know that – at least for some time – you and your family will be able to survive thanks to your unemployment benefits and to other forms of social support. In the meantime, hopefully, you will be able to get a new job – maybe thanks to the help from a public employment agency – or will at least be admitted into some publicly sponsored training program increasing your probability to get a new job.
Imagine that, instead of being fired, you get sick. Luckily most of the costs for your care will be covered by the public healthcare system. You will continue receiving your salary (with a reduction as the length of the period of sickness goes beyond a certain number of days) for at least a few months, typically until you can go back to work. If your illness is really serious, at some point you will not receive compensation but you will keep your job unless you stay away from your workplace continuously for a very long period. Should you lose your job, you will still be able to rely for a while on unemployment benefits and on additional forms of social support. Your family will be suffering of course, but at least you will be able to “gain some time” to find a solution.
Now imagine a different scenario. You lose your job. You get one month severance pay but no unemployment benefits. The labor market is hardly creating new jobs, so you have a high probability of not finding a good job and will have either to accept to be unemployed for a long period of time or to work in badly paid temporary jobs, maybe in very dangerous working places (because nobody is in charge of checking working conditions). In case you choose not to risk and to try looking for safer jobs, most likely during your unemployment period you will not receive any training and certainly no support from (non-existing) public employment agencies.
Or, what if you are sick and all healthcare costs fall on you. If you have a private health insurance you get some assistance. If not, you have to dissave in order to get some treatment. You receive one month of salary, after which your employer is free to fire you without having to give you any compensation. So you suddenly find yourself sick and not only unable to help your family but being a burden for it, with no public support and no income. To be fair, you might receive some sort of assistance, after you have applied to the government for support as a needy household if your situation has deteriorated so much that you cannot ensure even your subsistence (maybe by selling assets). However, this support is typically not that high.
This second case is not that of a fictional country. It is a representation of the conditions of most workers in Georgia.
If you keep this in mind, you will not be surprised looking at the following pictures taken from the latest EBRD (European Bank for Reconstruction and Development) Transition Report, titled: “Crisis and Transition: the People’s Perspective”. The tables and pictures included in the report are based on a series of household surveys conducted by the EBRD in a number of transition countries plus a few selected countries of Western Europe. The aim of this study was to study how the crisis had affected household’s welfare in order to draw some conclusion about the potential vulnerability of countries and households to future crises.
Figure 1.
Source: EBRD Transition Report 2011
In this first picture Georgia (in red) stands out as very much above the regression line. It is what is defined as an “outlier”. In this case, being an outlier means exactly that Georgian households, despite having been themselves hit by a relative smaller number of negative events, appear to have suffered much more than households in similar situations in other countries. In other words, they were forced to cut their consumption much more than households in other countries.
The second picture (below) allows us to see where Georgian households had to cut their consumption. Of course, cutting the consumption of luxury goods is not the same as cutting the consumption of food or healthcare. Looking at the second picture, the situation in Georgia appears even worse. Most households have had to cut exactly where one would hope they had not to: staple food consumption and visits to doctors.
Neither of these cuts bode well for the future of Georgian households, as they are likely to have long lasting (negative) effects. Especially as a new world crisis seems approaching.
Figure 2.
Source: EBRD Transition Report 2011
Why this discussion about Georgia and safety nets? The reason is because for some time now Georgia has been presented consistently as a showcase country with an impressive reform track (including an extremely liberal labor market reform that has drastically reduced all forms of workers’ protection) and equally impressive growth rates.
Much less has been said about how Georgian people have been affected by these reforms. For sure the picture that emerges from the EBRD study is of a country where households are extremely vulnerable to any slowing down of the economy or worsening of the macroeconomic conditions, much more than in most other countries.
Again, looking at the EBRD study, we can see that this is related to at least two factors: on the one hand the extremely weak safety net provided by the state; on the other hand, the limited success (so far) in translating high growth rates into a substantial amount of new, “good quality” jobs. This is what led the EBRD, after presenting these results to suggest the following two key priorities for the Georgian government: “…to create a basis for export led growth… […] but also to establish an effective social safety net”.
I would like to conclude with my personal answer to the question: “who needs a safety net?” The answer is a lot of people, I would say, especially in times of crisis like the current. After all, not even the best acrobats would dare to perform all the time without it, especially when they are trying their most dangerous performances for the first time and when preconditions are less than perfect. Why? Because the cost of failure would be too high. Like in the case of acrobats – even more, as they are not risking their own lives – policy makers have the responsibility of taking into account in their evaluations what could go wrong and think of ways to minimize negative impacts on the population.
Most economists would agree that only a sustainable increase in the welfare of citizens (including the most vulnerable ones) is the true sign of development of a country in the long run. Assuring this, as someone sometimes seems to forget, requires also creating and maintaining – especially when markets are less than perfect, a solid social safety net.
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The Distributional Impact of Austerity Measures in Latvia
For a country of its size, Latvia was mentioned in the last decade’s macroeconomic discourse remarkably often: first, for its exceptional growth up to 2007, then – for a dramatic GDP contraction in the aftermath of the 2008 financial crisis, and for the so-called “internal devaluation” policy that was the cornerstone of Latvia’s recovery strategy. Now, when GDP recovery is underway for 9 quarters, Latvia is held up as an example of a country that paved its way out of the crisis with decisive and timely budget austerity measures. The size of budget consolidation package was remarkable, reaching almost 17% of GDP in 2008-2011. Today, when there is so much talk about austerity in the context of the Eurozone debt crisis, Latvian consolidation experience is of particular interest. In this brief, we are looking at the distributional impact of selected implemented austerity measures, using a microsimulation tax-benefit model EUROMOD. Our results suggest that the impact of these measures is likely to have been progressive, meaning that rich population groups are bearing a larger part of the burden.
From Boom to Recession
The “Baltic Tigers” – a term coined to praise the Baltic countries for their dynamic development in the 2000s, especially after their accession to the EU in 2004. During 2004-2007, average annual GDP growth in the Baltics exceeded 8% (in Latvia average growth was 10%). The growth was to a large extent driven by an externally financed credit bubble, leading to overheating of the Baltic economies: inflation was skyrocketing, unemployment was at historically low levels, and current accounts posted double-digit deficits. Before the outbreak of the crisis, the Latvian economy was in the most vulnerable position: Estonia was better situated thanks to prudent fiscal policy implemented in the “good” times, whereas Lithuania was less exposed thanks to its private sector being relatively less indebted.
The growth slowdown in Latvia began in 2007 and was initially triggered by the government’s adopted “anti-inflation plan” and the two of the biggest banks’ actions aimed at restricting credit expansion. Altogether, this initiated a decline in real estate prices. By December 2007, the average price of a square metre in a standard-type apartment in Riga had fallen by 12% from its peak in July (Arco Real Estate, 2008). Construction, retail trade and industrial production growth slowed down in the second half of 2007. GDP quarter-on-quarter growth approached zero by end-2007 and turned negative in the 1st quarter of 2008. In August 2008, the second largest Latvian commercial bank, domestically owned Parex Bank, faced deposit run and was unable to finance its syndicated loans, and in November 2008, the Latvian government took the decision to nationalize the bank. By the 3rd quarter of 2008, GDP quarter-on-quarter contraction exceeded 6%. The budget revenues lagged behind the expenditures, resulting in a gradually growing budget deficit, which reached about 5.5% of GDP in the 3rd quarter of 2008 (see Figure 1).
Figure 1: Year-on-year growth of general government budget total revenues, tax revenues and expenditures, %; seasonally adjusted budget balance, % of GDP
Source: Eurostat, authors’ calculations
In circumstances where the fiscal position was quickly deteriorating but world financial markets were frozen, the Latvian government was forced to seek financial assistance from international lenders. After tough negotiations in November and December 2008, Latvia received a 7.5 billion euro (about 1/3 of GDP) bailout facility from the IMF, the European Commission, the World Bank and the Nordic countries. Latvia received the funding in a series of tranches, with the transfer of each tranche being subject to implementation of a strict reform package agreed with the lenders.Given that introduction of the euro in 2014 remained the Latvian government’s target, one of the key elements of the reform programme was maintaining the lat’s peg to the euro. Therefore, the Latvian government had to accept especially strict and wide-ranging budget consolidation measures.
Budget Consolidation
The total size of budget consolidation achieved in 2008-2011 was impressive: overall, the fiscal impact of the reforms is estimated at 16.6% of GDP (Ministry of Finance of Latvia, 2011). Under the pressure of international lenders, budget consolidation was front-loaded and was achieved astonishingly fast – the fiscal impact of the reforms implemented in 2009 reached almost 10% of GDP, whereas the impact of 2010 and 2011 year measures was much smaller – 4.1% and 2.6%, respectively (see Figure 2).
Figure 2: Size of the implemented consolidation measures and budget deficit outturn, % of GDP*
* Budget deficit in 2011 is the Bank of Latvia’s autumn forecast
Source: Ministry of Finance, Bank of Latvia, Eurostat
Yet the way the consolidation was done was rather chaotic. The 2009 consolidation was mainly implemented by expenditure cuts, including strong wage and employment reductions in the public sector (public pay and employment cuts were continued in the following years, wages were cut by 15-20% in each round and most bonuses were abolished). On the revenue side, the government stuck to the goal of shifting tax burden from labour to consumption, thus the consolidation was mainly achieved by raising indirect taxes, while the personal income tax was reduced. Another line followed by the government at the time was to strengthen support to those affected by the crisis, for example, the duration of unemployment benefits was increased.
Nevertheless, by the time preparation of the 2010 budget started, it became clear that in circumstances of continuing GDP fall and peaking unemployment (in 2009, GDP fell by 17.7%, and the rate of unemployment reached 17.1%), the reduction in labour taxes could not be sustained while the social budget could not bear the burden of growing expenditures. Consequently, the reduction in the personal income tax was reversed (the tax rate was raised even above the pre-crisis level). To consolidate the social budget, the government implemented an across the board cut by introducing ceilings on the size of many benefits. In 2011, the tax burden on labour was further increased by raising the rate of mandatory social security contributions.
Budget consolidation was done under the pressure of the crisis and the reform package was designed in a great rush. What also may not be disregarded, is that the three years – 2009, 2010 and 2011 – were election years in Latvia: in 2009, there were local government elections, in 2010 – parliamentary elections and in 2011 – parliamentary re-elections . Elections have arguably affected the composition of implemented austerity measures. Thus, in June 2009, just ten days after local government elections, amendments to the Law on State Pensions were passed, which stipulated that old-age pensions should be cut by 10%, but pensions to working pensioners should be cut by 70%. This decision caused a strongly negative public reaction and on December 21, 2009, the Constitutional Court ruled that the government’s decision was unconstitutional arguing that the state must guarantee peoples’ right to social security. In the following budget consolidation rounds, even in the face of convoluted IMF recommendations to find a constitutional way of ensuring sustainability of the pension system (IMF, 2010), the government remained strictly opposing any pension cuts.
The mix of implemented reforms is crucial not only because it determines the effectiveness with which the budget consolidation is achieved. What is equally important is that the mix of reforms affects the distribution of costs of the crisis and shapes the economic recovery path. The consequences of the crisis – the dramatic rise in unemployment and wage reductions in the private sector – had a strong impact on incomes, yet policy makers can do little to directly affect this process. On the other hand, policy makers can offset or aggravate those effects by implementing reforms, such as those that made up the austerity packages. In this brief, we assess the distributional impact of selected austerity measures, which were implemented in 2009 – 2011.
Modelling Approach and Limitations
We use the Latvian part of the tax-benefit microsimulation model EUROMOD and follow a similar approach as that taken by Callan et al (2011). We limit our analysis to reforms in direct taxes, social contributions, and cash benefits . In particular, the following austerity measures are included in the analysis:
- removal of income ceiling for obligatory social insurance contributions (in 2009);
- increase in the rate of social insurance contributions for employees, employers, and self-employed (June 30, 2011);
- reduction of tax exemptions (July 1, 2009);
- increase in the rate of personal income tax (2010);
- introduction of benefit ceiling for unemployment benefits (2010), maternity, paternity, and parental benefit (November 3, 2010);
- cuts in state family benefit (2010);
- cuts in child birth benefit (2010);
- reduction in the amount of parental benefit by limiting eligibility to non-working parents only (May 3, 2010);
- making stricter income assessment criteria for guaranteed minimum income (GMI) and reducing amount of the GMI benefit for some groups (2010).
We assess the distributional impact of these austerity measures by comparing two alternative scenarios:
- the baseline scenario – simulation of 2011 tax-benefit policy system (with austerity measures implemented), and
- the counter factual scenario – simulation of tax-benefit policy system that would have emerged in 2011 in the absence of austerity measures.
If a policy was changed as a part of the austerity package (e.g. income tax increase), we implement a pre-austerity policy (e.g., reduce the income tax to its pre-austerity level). However, if the changes in the policies were regular (e.g. an increase in minimum wage that was planned long before the discussion of austerity measures had started) or not related to austerity measures (e.g. increase in duration of unemployment benefit) we include them in the counterfactual scenario, as well as in the austerity package scenario. By defining the counterfactual scenario in this manner we focus on the impact of austerity measures only holding other things equal.
Despite Latvia is one of the countries where the size of the austerity package was especially large, the distributional effect of the implemented measures has not been analysed neither before nor after the policies had been implemented. Until recently Latvia didn’t have a national microsimulation model which could be used to assess the impact of taxes and benefits on household income. This paper is the first attempt to do this.
However, our analysis is subject to some drawbacks. First, EUROMOD’s input data is based on the European Union Statistics on Income and Living Conditions 2008 (with the income data referring to 2007). We adjust 2007 incomes up to 2011 using updating factors based on the aggregate evolution of such incomes according to national statistics. However, we do not adjust for the changes in the labour market that happened during this period. Therefore, we estimate the effect of austerity measures on data that represent the population with pre-crisis labour market characteristics (e.g. relatively low number of unemployed people).
Second, the analysis is limited to the direct impact of the implemented measures, disregarding the secondary effects such as e.g. behavioural responses of people on the implemented policies.
Results
The simulation results suggest that the impact of the analysed austerity measures was progressive with top income groups being the most affected (see Figure 3). The six countries considered in Callan et al (2011) show different degrees of progressivity: Greece demonstrated a clearly progressive impact, while Portugal was the only country where the effect was regressive. The result for Latvia is likely to be a consequence of introduced ceilings on contributory benefits, as well as the increases in income tax and social insurance contributions. While income tax in Latvia is flat (except for a relatively small untaxed personal allowance), the lowest income deciles contain proportionately more unemployed people and pensioners.
Figure 3: Percentage change in household disposable income due to austerity measures by income deciles
Source: based on own calculation using EUROMOD
Higher progressiveness was observed for households with children (see Figure 4), which is explained by the introduction of ceilings on child-related contributory benefits. At the same time, the impact on the households with elderly was more even.
Figure 4: Percentage change in household disposable income due to austerity measures for different types of households by income quintiles
Source: based on own calculation using EUROMOD
While the introduction of austerity measures made all income groups poorer, progressivity of the impact reduced income inequality. The Gini coefficient of the counter factual scenario is 1 percentage point higher than that of the base scenario. After implementation of the austerity measures, the poverty line decreases because the median income decreases. As a result, poverty rates using relative poverty lines decreased. The poverty rate of the elderly was affected the most, because pension income was not cut and pensioners became relatively better off as compared to other population groups. However, if measured against the fixed poverty threshold, the poverty rate increased in all population groups (see Table 1).
Table 1: Poverty rates and Gini coefficient before and after implemented austerity measures
Source: based on own calculation using EUROMOD
Concluding Remarks
The austerity measures analysed in this paper have had a progressive impact, with the richest population groups likely to be bearing most of the costs. This result should be interpreted with caution. It should be taken into account that we do not model all of the austerity measures that were implemented in 2009-2011. E.g., we do not model the impact of changes in VAT rates, which is likely to have been quite strong and regressive.
Latvia is a society with extremely high income inequality. For example, the income quintile share ratio calculated by the Eurostat (S80/S20), which measures income inequality, in 2009 was the second highest in the EU (6.9 as compared with an EU average of 4.9). It is unlikely that the progressive impact identified in this paper will significantly reduce income inequality gap in Latvia relative to other European countries.
References
- Arco Real Estate (2008). Real estate market overview (Sērijveida dzīvokļi, 2008. gada decembris)
- Callan, Tim, Chrysa Leventi, Horacio Levy, Manos Matsaganis, Alari Paulus & Holly Sutherland (2011). “The distributional effects of austerity measures : a comparison of six EU countries”, Social situation observatory, Research note 2/2011.
- International Monetary Fund (2010). Republic of Latvia: Second Review and Financing Assurances Review Under the Stand-By Arrangement, Request for Extension of the Arrangement and Rephasing of Purchases Under the Arrangement and Request for Waiver of Nonobservance and Applicability of Performance Criteria. IMF Country report No. 10/65, March 2010.
- Ministry of Finance of Latvia (2011). Budget consolidation in 2008-2011 (Veiktā budžeta konsolidācija laika posmā no 2008.-2011. gadam)
Can the Baby- and Woman-Friendly Maternity Wards Save Lives?
Improving the health and well-being of mothers, infants and children has been an important public-health goal for many countries, which is reflected in the Millennium Development Goals (4 and 5), set by the United Nations. The well-being and health of mothers, infants and children determine future population health and thus public health challenges as well as economic development prospects. Although Ukraine and the other countries of the Former Soviet Union have fared well compared to the less developed countries of Asia, Africa and Latin America, their maternal and infant mortality and morbidity rates are 3 to 5 times higher than those in the European countries (including those of the Former Socialist block). There are many factors behind this situation. Nevertheless, a lot can be done to improve maternal and infant health by simply changing the way labor and delivery services are provided. New evidence-based medicine (EBM) standards introduced by the Mother and Infant Health Project (MIHP) are more baby- and woman-friendly and include: partner deliveries; avoidance of unnecessary C-sections, amniotomies and episiotomies; use of free position during delivery; immediate skin-to-skin contact; early breastfeeding; and the rooming-in of mothers and newborns. The impact of the Project culminates with 3 mothers’ and 11 newborns’ lives saved every two years in an average participating region.
Infant mortality/morbidity has often been a focus of health economics and medical research as a major indicator of a country’s well-being. In contrast, maternal health outcomes have been much less investigated. There are several potential reasons for such negligence. One is that the rates of maternal deaths are quite low in developed countries. The second is attributed to the difficulty of measuring maternal health outcomes in developing countries where the rates of maternal mortality are particularly high. Nevertheless, the issue of maternal health attracts considerable attention from society due to the fact that most of maternal deaths and health deteriorations are preventable. Moreover, recent evidence demonstrates that improvements in health outcomes for mothers and infants are not as much related to the availability of care (structural quality), as to the way this care is provided (process quality) (Barber and Gertler, 2002). Furthermore, some studies find that access to low quality providers in fact contribute to higher child morbidity and mortality (Sodemann et al., 1997).
Although the population health in Ukraine compares favorably to the situation in the developing world, it is still lagging far behind the developed countries in terms of maternal and infant mortality and morbidity. During the latest years, the level of anemia among pregnant women has increased 4.5 times, maladies of genital urinary system about 3 times, and diseases of blood circulation system 2 times. The average maternal mortality ratio fluctuates around 18-22 women per 100,000 live births, which is 3.5 times higher than in the EU. At the same time, infant mortality (9.5/1000) is two times higher than that in the EU, while the rate of stillbirth (16.89/1000) is four times higher. Additionally, the incidence of congenital anomalies of newborns has increased over time and reached the number of 2878 per 100,000, which is 77% higher than the EU average.
Another alarming problem related to maternal health is persistently high rate of abortions, which most likely originates from ignorance in modern family planning methods. In contemporary Ukraine, 71% of pregnancies end up in abortions. Although the number of abortions decreased twice between1991 and 2003 (from 1532/1000 live births to 728/1000 live births respectively), the incidence is still 3.5 times higher than that in the EU (Center of Medical Statistics of Ukraine 2007).
Mother and Infant Health Project Description
The Mother and Infant Health Project is an eight-year project advocating evidence-based medical practices aimed to improve women’s reproductive and newborns’ health. With funding from the USAID and private sources, and with the support from the Ministry of Health of Ukraine, the project has been implemented by the JSI Research and Training Institute. The first phase of the project was initiated in September 2002 in four regions of Ukraine, but the first four maternities joined the Project in mid-December 2003. By the end of 2006, the Project had expanded to 20 maternity hospitals in twelve pilot regions.
Following the Millennium Development Goals (MEU, 2005), the MIHP pioneers to introduce new evidence-based medicine (EBM) standards: partner deliveries; avoidance of unnecessary C-sections, amniotomies and episiotomies; use of free position during delivery; immediate skin-to-skin contact; early breastfeeding; and the rooming-in of mothers and newborns. In addition, the Project actively supports the provision of training on effective perinatal technologies for the staff of the MIHP maternities, development of “centers of excellence” that serve as models in training/education of medical practitioners of the corresponding oblast, and organizing a health awareness campaign on healthy lifestyles. The MIHP also aims to reinforce liaisons with local governmental institutions.
Furthermore, the Project works on integration of the EBM standards into a package of perinatal practices throughout Ukraine. It also targets revision of the current curricula for medical universities and colleges in order to increase the evidence base of educational programs for medical students and health care providers.
The MIHP in Ukraine belongs to a family of maternal and infant health improving initiatives throughout the world and builds upon their experience, JSI Mother Care (1998-2000) being the largest among them. However, the MIHP in Ukraine is unique both with respect to the institutional setting and to its scope and length, which allows for rigorous evaluation. Most of the earlier projects implemented by the JSI have mainly focused on specific issues (e.g. pregnancy of adolescent girls in Uganda and Zambia, anemia in Malawi) and have been short-term (the longest have been two-year projects in Egypt, Pakistan, and Zambia).
The Impact of the Mother and Infant Health Project
The evaluation of the impact of the first phase (2002-2006) of the Mother and Infant Health Project in Ukraine allows for an identification of improvements in the maternal and infant health outcomes due to enhancements in the quality of labor and delivery services. The identification of the quality improvement effect has been possible for two reasons. First, the basic perinatal and obstetrics care is universally available in Ukraine. Hence, the estimated impact of the small region participating in the MIHP can be attributed to the improvement in medical technologies rather than the availability of the services per se. Second, the variation in the project participation over time and across regions allows for control of the overall population health trend in the country.
Taking into account the effect of the other maternal health programs and personnel training outside the Project, Nizalova and Vyshnya (2010) find that the MIHP impact is in general health improving. Decreases in both maternal and infant mortality and morbidity in participating regions are more pronounced after the start of the Project. Among the infant health characteristics, the MIHP impact is observed for stillbirths and infant mortality and morbidity resulted from deviations in perinatal period and congenital anomalies.
Concerning maternal health, the MIHP is most effective in combating anemia, blood circulation, veins, and urinary-genital system complications, and late toxicosis. The analysis suggests that the effects are due to early attendance of antenatal clinics, lower share of C-sections, and greater share of normal deliveries.
For some outcomes (maternal mortality, normal deliveries, and anemia) there exists a significant effect of the MIHP trainings (without joining the Project), although it is about twice as small in magnitude for normal deliveries and anemia than the direct MIHP impact.
Cost-Benefit Considerations
A comprehensive cost-benefit analysis of the MIHP project is limited, since the majority of maternal and infant health indicators are hard to assess in monetary terms (e.g. increase in early neonatal visits of mothers; decrease in the number of cases of late toxicosis and complicated deliveries; decrease in infant morbidity due to various reasons etc.). Therefore, the focus is on the most “tangible” cost effectiveness indicators: (i) average annual per maternity cost of the Project and (ii) average annual per maternity “tangible” benefits.
The average annual per maternity cost is about 60,000 USD and it is calculated as an overall cost of the first phase of the project – 6 million USD – distributed over 20 treatment sites during 2002-2006, including the first year of the Project setup. Set of “tangible” benefits includes savings due to (i) a switch from C-sections to vaginal deliveries (cost savings of around USD 2,500 per maternity per year), (ii) a switch away from medicine-intensive ways of leading both C-sections and vaginal deliveries (around USD 65,000 per maternity per year), and (iii) saved lives of mothers and infants due to the implementation of the MIHP practices (around USD 5.8 million per maternity per year ).
Overall, the project cost to benefit ratio is 1 to 97 (60 to 5,847 thousand USD) if one takes into account the value of lives saved and it is 1 to 1.08 (60 to 65 thousand USD) if one considers only cost savings due to change in C-section and vaginal delivery practices and the switch away from C-sections to vaginal deliveries. The latter represents the lowest bound of the Project’s benefits since it does not take into account any health-improving impact of the MIHP. Although the range is quite wide and this preliminary calculation suffers from several limitations, it seems unlikely that given the estimated impact the true costs would exceed the true benefits.
References
- Barber, Sarah L and Paul J Gertler. 2002. “Child Health And The Quality of Medical Care.” University of California-Berkeley Working Paper .
- Giergiczny, Marek. 2008. “Value of a Statistical Lifethe Case of Poland.” Environmental and Resource Economics 41 (2).
- MEU. 2005. “Millennium Development Goals. Ukraine.” Ministry of Economy of Ukraine .
- Olena Y. Nizalova & Maria Vyshnya, 2010.”Evaluation of the impact of the Mother and Infant Health Project in Ukraine,” Health Economics, John Wiley & Sons, Ltd., vol. 19(S1): 107-125.
- Sodemann, M., M.S. Jakobson, I.C. Molbak, I.C. Alvarenga, and P. Aaby. 1997. “High mortality despite good care-seeking behavior: a community study of childhood deaths in Guinea-Bissau.” Bulletin of the World Health Organization 3 (75):205–12.
Privatization in Belarus – Obstacles and Perspectives
For a long time Belarus considered privatization as a minor factor in influencing the economy’s development, competitiveness and effectiveness. The former economic model relied on concessional loans and donations from Russia and various international organizations. The 2011 financial crisis led to the breakdown of this model and forced the authorities to reconsider privatization. A draft of a new law on investment has been prepared, which is aimed at increasing foreign capital inflow to the country. However, it does not contain sufficient measures to significantly raise the investment attractiveness. In turn the lack of such attractiveness can have a very negative effect on the economy in the near future.
Belarus is right now facing a currency crisis primarily due to three factors:
- A growing deficit of trade and payment balances;
- The National Bank’s continuing Belarusian ruble emission partly because of pre-elective directive wages’ raise;
- A lack of foreign currency reserves required to keep the USD exchange rate at BYR 3100 level.
However, the key problem is a growing negative balance of payments, which in January-June 2011 amounted to USD (-1032.6) million against USD (-82.2) million in January-June 2010.
The Belarusian ruble devaluation, which occurred in May 2011, managed to improve the trade balance situation and gradually lead to export earnings growth. That in turn reduces the current account deficit, which amounted to USD (-1630.4) million in the second quarter of 2011 against USD (-3657.2) million in the first quarter 2011.
Negative foreign trade balance mostly forms negative balance of payments of the country, and problems with external payment capacity are likely to occur under conditions of trade deficit preservation. Moreover, taking into account that the main repayment share of external debt should be paid in 2012-2014 it is necessary to attract additional funding sources.
Table 1. External debt repayment scheme
For this to be feasible privatization as a major long-term capital raising instrument will be required for the following reasons:
- Belarus will not be able to borrow in the external markets in the near future. This is due to impossibility of attracting loans from international organizations as well as extreme expensiveness and inexpedience of sovereign debt securities placement in global stock markets.
- Before the 2011 crisis, public and private companies were able to attract bank and state financing programs’ sources for the financing of their activities. However, the unstable economic situation in the country has forced the authorities to cut the state programs’ funding (BYR 12 trillion instead of requested BYR 36 trillion, while BYR 22 trillion were spent in 2011) in order to prevent further inflation and to provide a budget surplus. Moreover, the economic crises resulted in a decline in domestic demand of the population and the corporate sector simultaneously, with reduced domestic savings levels as a consequence. During the first eleven months of 2011 savings dropped by 25% in USD terms in comparison to the corresponding period of the previous year. These occurrences in the economy make a search of a strategic partner through additional issue of shares or mergers with other agents the only source of financing attraction for state and private companies.
Speaking about the current situation, it should be noted that Belarus planned to get around USD 3 billion from privatization in 2011. 178 assets were to be sold according to the privatization plan. However, just around 38 assets were sold in 2011 and the country managed to gain around BYR 150 billion (USD 17.6 million) from that. Thus, the result cannot get positive evaluation right now.
The main reasons for the slow privatization process and weak foreign capital inflows are the following:
- The multiplicity of agencies responsible for privatization. There are too many responsible decision-makers, which potential buyers have to contact. In addition, it is not very clear which agency is responsible for this or that asset. The State Property Committee and the National Agency for Investments and Privatization (NAIP) supervise the state asset sales today. However, ministries and local authorities are also responsible for privatization plan accomplishment.
- Difference in asset valuation methods. Investors, while analyzing any investment project, tend to focus on the cash flows that the project will be able to generate and how soon the costs will be covered. The Belarusian side values the asset according to its’ book value, below which the price cannot fall. This often results in large price differences.
- Additional requirements. The presence of additional requirements is a common phenomenon, but only when the price negotiations are more flexible. But it distracts investors in case the requirements are followed by a fixed overestimated price.
- Lack of transparency. Periodically the deals are announced, which were closed not during the auctions or tenders but after the closed backroom negotiations. That also affects negatively investors’ opinion about the country
- High share of public sector. Private sector is mostly represented by small and medium businesses. Thus, the strategic investors’ interest in them is initially lower. Moreover, they are unable to invest by themselves due to a lack of resources.
In addition, the authorities and enterprise management demotivation in the privatization process, an undeveloped culture of IR and consulting services usage, and the fact that it is often non-controlling stakes that are put up for sale, are also obstacles in the process.
These are the main problems influencing the foreign capital inflow rates. Their solution and elimination should increase the economy’s investment rates as there is an interest in the country’s assets and it is high enough.
As was mentioned earlier, the sale price of an asset is estimated according to its’ book value in Belarusian rubles. The national currency devaluation, which occurred in May and October 2011, has significantly reduced assets’ real value in USD terms and therefore a sharp drop in prices occurred. Starting from March 2011, the national currency depreciated by 181%, and the fall in real value of assets on sale was comparable. The analysis of transactions, which were closed during the auctions held in 2011, showed that the companies acquired by the investor were generally highly undervalued even in the beginning of 2011.As a result of devaluation, the ratio of asset price to revenue (P/S) dropped by 1.67-1.8 times. OJSC “Zhlobinmebel” (P/S=0.3 January 2011, P/S=0.18 in June 2011), OJSC “Vitebskles” (P/S=0.37 – January 2011, P/S=0.2 – June 2011) .
On the other hand, in accordance with Presidential Decree #476, the revaluation of fixed assets should be done by January 1, 2012 and adjusted to PPI, which equaled to 82% in October, 2011. Such adjustment will still not be able to cover the depreciation resulting from the devaluation. Therefore, there will be a gap between the announced corrected asset price and its real value at least for another year.
Nowadays, the demand is formed by Belarusian export-oriented companies. Their products have become more competative in the markets as a result of devaluation and have caused some growth in earnings. Consequently, they are ready for vertical and horizontal integration with attractive companies operating in the local market in order to expand the production and increase their niche in the global markets.
As for foreign investors, macroeconomic stabilization is necessary in order to make them wanting to enter the Belarusian market. Moreover, foreign buyers are attracted by the strategic Belarusian companies rather than by the small and medium business. This is because they are then able to generate sufficient profit volumes even in the short-term period.
Conclusion
The privatization process will be much more active and intensive in the forthcoming 2012, in comparison to what we have seen during 2011. This is determined on the one hand by a great need in external capital and on the other hand by sufficiently favorable acquisition conditions. However, obviously the privatization process and plan should be reviewed and optimized.
It might be more efficient to put on sale, not just companies’ shares, but also controlling interest as it should increase buyer interest.
It is also possible to sell assets at a minimum fixed price (in case it has losses and no perspectives with current owner), or the authorities could reduce the amount of requirements which accompany the transaction.
Finally, it should be noted that the privatization of small companies will not generate sufficient amounts of foreign capital to the country. In order to achieve that goal, Belarus will have to sell some large strategic assets. It already sold the state’s controlling interest of OJSC “Beltransgaz” to OJSC “Gazprom” for USD 2.5 bln. As for other assets, it is most likely that these will be 51% of shares sale of OJSC “MTS”, 51% shares sale of OJSC “Naftan” in exchange of USD 1 billion syndicated loan issued by “Sberbank Russia” and EABR, as well as a merger of OJSC “MAZ” with Russia’s corporation “Russkie Mashiny” or OJSC “KAMAZ”.
▪
References
http://nbrb.by/statistics/BalPay/Analytical/Current/
http://banki.bel.biz/?p=4167
http://www.interfax.by/news/belarus/101635
http://belstat.gov.by/homep/ru/indicators/doclad/2011_11/6.pdf
http://www.gki.gov.by/about/press/news/e4fc4311733e0af1.html
http://minfin.gov.by/rmenu/departament/itogi-emit/itogi-oao/
http://www.president.gov.by/press127520.html
Russia and the WTO
Eighteen years after the start of the accession process, Russia is closer than ever to joining the World Trade Organization (WTO). The negotiations have been long and hard as Russia had to agree the accession terms with 57 out of the 153 WTO member countries which formed the working group. Moreover, the number of goods for which the extent and timeframe of the change of Russian tariffs were agreed exceeded 10,000. The negotiation team led by Maxim Medvedkov has done an immense amount of work and found compromises on sensitive issues such as pay for the flights of foreign planes over Siberia, compensating European producers for the discriminatory law on industrial assembly, the amount of support for the agricultural sector, access to the market of banking services, etc. Now, all these differences have been ironed out and the WTO has agreed with all the participants, and put on the table the final terms of Russia’s accession.
Terms of Accession
It has to be noted that the change of tariffs after Russia’s accession to the WTO will be insignificant. Average tariffs on goods after all the agreements have come into force will decrease to 7.8% from 10% in 2011.
The tariffs on agricultural goods will drop to 10.8% compared with the current level of 13.2%, and for manufactured goods from 9.5% to 7.3%. The duties on some goods will, however, drop significantly. For example, the tariff on new cars will be cut by half from 30% today to 15%. On the other hand, one has to bear in mind that the agreed decrease of all tariffs will not happen overnight after the Russian accession. It will rather take place gradually at a rate which has also been agreed on with the WTO members. The tariff for new cars will drop to 25% immediately after accession and will remain at that level for the next three years before the cuts resume at an annual rate of 2.5% over the following four years to reach the targeted level of 15%. Russia has no commitments to reduce tariffs any further. The tariffs on used cars up to 7 years old will be fixed at 25% at accession and will not change over the next five years before being cut to 20% over the following two years. Duties on cars older than 7 years will not change at all. On the whole, tariffs will be changed completely immediately upon accession only on one-third of the goods. For many goods the process will extend over three years, and for some over 8 years after accession.
Not only trade in goods, but also service and foreign direct investment spheres will be liberalized. One of the most difficult negotiation items was the banking sector, where some WTO member countries (notably the USA) demanded a total opening up of the Russian market of banking services to foreign financial and lending institutions. Moscow, for its part, insisted on preserving the current situation where only the subsidiaries and not branches of foreign banks operate in the Russian market. The difference between the former and the latter is that the activities of subsidiaries on Russian territory are regulated by the Russian Central Bank, while branches are regulated by the laws of the country of origin. The Russian position prevailed, which means that the situation for foreign banks will not change and the cost of entering the Russian market will remain at the current level. Accordingly, the cost of banking services for Russian clients will not change. This is not good news for Russian small and medium-sized enterprises which had hoped that a massive entry of foreign banks could help bring down the interest rates on loans.
Major changes may take place in the insurance market when Russia allows branches of foreign insurance companies. However, a nine-year transitional period appears to be enough for all the stakeholders to prepare themselves.
Assessment of the Consequences of Russia’s Accession to the WTO for the Economy
The question that is uppermost in the minds of all Russians is whether the economy stands to gain or lose as a result of WTO accession. On the one hand, opponents of accession point to the not very successful experience of accession to the WTO of some former Soviet republics. These opponents paint lurid pictures of the social consequences of the closure of a large number of Russian enterprises. By contrast, the advocates of accession cite the success of China whose export-led growth accelerated significantly after the country joined the WTO. Time will tell what the results of a WTO accession will be for Russia. The result will in many ways depend on well-thought-out and coordinated actions of the Russian federal and regional authorities. In the meantime, we can only talk about what we expect from accession and what its potential consequences may be. The Russian government and the World Bank have conducted several major studies, seeking to determine the economic consequences of a WTO accession. While there are some discrepancies in evaluating the quantitative changes in specific sectors and at the economy-wide level, researchers more or less agree in qualitative terms. The general consensus is that the changes in outputs, consumption, prices and welfare due to the new tariff agreements are likely to be fairly small. Because the overall reduction of import tariffs in Russia will be insignificant, one may expect that changes in specific sectors, too, will not be dramatic (within plus-minus 1-3% of the base level).
CEFIR jointly with the Belgian TML Centre and the German ZEW with the support of the European Union Seventh Framework Programme, recently build a general equilibrium model of the Russian economy SUST-RUS (CEFIR 2011) which makes it possible to assess the effect of a Russian WTO accession on specific sectors. Several scenario calculations have been made to model the short term (one or two years after the reduction of all the tariffs) and long-term (five or six years after the reduction of all the tariffs) effects of a Russian WTO accession. The results of the scenario modeling should be seen as an indication of the direction of market processes caused solely by a WTO accession without taking into account any other possible changes in the economic environment (for example, a change of energy prices, the strengthening or weakening of the ruble against the leading world currencies, changes in the domestic market, etc.).
The short-term scenario assumes only a change of the tariff timetable. The long-term scenario has a further assumption concerning the return on foreign direct investments for the business service sector. Business services include banking insurance, financial services, transport services, wholesale trade, etc. Some terms of Russia’s WTO accession pertain to the business service sphere and envisage considerable liberalization of foreign companies’ access to these sectors. One can expect that lower barriers to entry would push down prices in these sectors and make them more accessible for Russian enterprises, which in turn would reduce their costs, boost production and create more jobs. The general equilibrium modeling of this mechanism assumes a conservative reduction of barriers for foreign investments of about 10% of the current level.
According to CEFIR’s results, the potential growth of welfare in the economy caused by a WTO accession in the short term will be 0.4% per year, and in the long term 1% per year. Budget revenues will fall due to diminished tariffs, and there may be a dip in the rate of GDP growth in the short term. Model calculations show a significant change of the trade balance, possibly a reduction of the trade surplus to 10%. At the sectorial level, a WTO accession will reduce domestic prices of timber and articles made from wood, foodstuffs, transport means, as well as equipment, clothes, chemicals and petrochemical products by 1.5-2.5% in the short term and by up to 3% in the long term. This will increase consumption by between 0.2% and 0.4% in the short term and up to 1.5% in the long term. It has to be noted that the liberalization of the service sphere is a very important assumption of these calculations as it accounts for half of the long-term gains for consumers.
The World Bank has also carried out a study of the consequences of a Russian accession to the WTO in 2004 (Jensen et al, 2004). That study put the net positive gain from liberalization of tariffs at 3.4% of the GDP. That analysis was based above all on the economic effect from a change in import tariffs. Trade liberalization is historically associated with lower tariffs. Most sectors stand to gain from accession. Because the authors identify two main causes of the gains from liberalization – easier access to foreign markets and cheapening of the ruble in proportion to the change of tariffs – the sectors that will benefit are those which has a high share of exports, and which have not been heavily protected by tariffs to begin with.
The biggest beneficiary will be metallurgy, with a 25% increase in output and employment in ferrous metallurgy and 15% in non-ferrous metallurgy. The growth in the chemical and petrochemical industries can be up to 10% and in coal mining up to 6%. The significant gains predicted by the World Bank study owe something to the optimistic view of the possible terms of Russia’s accession to the WTO. For example, it assumed that all the import tariffs would be cut by 50% and all (100%) of the administrative barriers to investment in business services would be removed. More modest assessments of the potential gains for Russia in other studies reflect the smaller Russian commitments to liberalization of import tariffs and the services sphere. For example, CEFIR’s results show that steel-making enterprises will not experience difficulties after a WTO accession and may grow by about 2% in the long term.
Along with the cut of import duties, Russian producers will face tougher competition on the part of foreign goods for which prices will be cut. Accordingly, Russian producers will also have to cut their prices to be competitive. This is good news for consumers. Not all domestic producers will be able to cut their prices. The enterprises whose production costs turn out to be higher than the new prices, and which fail to cut their costs, will be pushed out of the market. The sectors where one can expect a drop in production are above all those which have long been protected against international competition by high import duties. CEFIR’s study has shown that in the short term, negative consequences may ensue for the food industry, pharmaceutical companies and textile enterprises which may see their output drop by between 0.5% and 2%.
According to the World Bank study, the biggest decline in output and employment may occur in the machine-building sector (12%) and in the food and light industries as well as in the construction-material industry (up to 7%). The above figures of decrease or increase refer to the summary effect from liberalization accumulated over a period of 7-10 years after a Russian accession to the WTO. Several studies have been devoted to the consequences of a WTO accession for regional economies. For example, World Bank experts (Rutherford and Tarr, 2006) point to positive, but uneven consequences of a WTO accession for Russian regions. The biggest beneficiaries from lower tariffs are likely to be the Tyumen region, the North Western District as a whole, and in particular, St. Petersburg, where welfare may increase by 1%. Low growth or no growth may be expected in the Central District and in the Urals. These results tally with the assessments of the consequences of WTO accession for the Russian regions made by the Independent Social Policy Institute (ISPI 2004) which also included some regions of the Volga Federal District among the high-risk regions.
Results of studies of changes in the labor market in the wake of WTO accession, generally accord with the other findings. The International Labor Organization (ILO 2003) predicts an average loss of 6000 jobs in industry in the year following accession and up to 1000 jobs in seven or eight years’ time. The biggest number of jobs will be lost in the light-industry sector (up to 15,000 during the transitional period). Such a drop in employment will hardly make any difference to the unemployment situation in the country as whole, but may differ from one region to another.
Most studies agree that Russia may gain from easier access for Russian enterprises to foreign markets after a WTO accession, but that the gain will not be great compared to the potential gain from the liberalization of the service sphere. There are not many export-oriented enterprises in the country, but they exist. There are about 6,000 export-oriented enterprises in the processing industry. These enterprises include chemical, metallurgical and high-tech enterprises, and are the most efficient and competitive producers in the country. These enterprises may be expected to pick up the slack in the labor market due to redundancies in sectors that will be affected by a WTO accession. The coordinating role of the state is very important in creating conditions for movement of labor. The gradual reduction of tariffs may dampen the social consequences of Russia’s WTO accession. In the regions where some production facilities are “doomed”, programs for retraining of labor must be launched without delay, especially in information technologies, and the services and skills required for starting a new business. The aim of such retraining should be to enable those who lose their jobs to be employed in other spheres of the economy. It is equally important to develop new forms of financing migration of the population within the country. The solution of this task may become one more – and very important – result of the WTO accession for Russia.
References
- CEFIR. 2011. SUST-RUS project. www.sust-rus.org
- ILO. 2003. “Social consequences of Russia accession to WTO.” Moscow office of ILO (in Russian)
- ISPI. 2004. “Russia’s accession to WTO: real and imaginary social consequences.” (In Russian)
- Jensen, Rutherford, Tarr. 2004. “Economy-Wide and Sector Effects of Russia’s Accession to the WTO.” World Bank
- Rutherford, Tarr. 2006. “Regional Impacts of Russia’s Accession to the WTO.” The World Bank