Working paper
TFP Estimates and Frontier-generated Production Function: A New Dataset for Political Science
What is governmental effectiveness on the regional level? How can the study of regional effectiveness help us understand the performance of the political, social and economic systems of the state as a whole? These questions are very important from both the theoretical and applied perspectives, and the Russian Federation, with its huge and diverse territory, provides extremely rich material to answer them. Serious institutional reforms in the public sector have been implemented in recent years, and the results vary substantially from one region to another. So, in Russia, we can study how general attempts to make government more effective - guided by federal policies - produce particular regional effects, and, conversely, how regions implement federal policy differently. Both views tell us something important about overall governmental quality.
Governmental effectiveness, though in a broad sense one of the oldest issues in political science and philosophy, is currently enjoying a renaissance. The quantity of recent publications and even a special academic structure - The Quality of Government Institute in Sweden – illustrate the current interest. However, researching governmental effectiveness poses serious difficulties, on both the conceptual and instrumental levels. Despite (perhaps even because of) the variety of available theoretical frameworks, the essential core notions of governmental effectiveness and good governance remain murky. Furthermore, scholars disagree about what effectiveness and efficiency mean in a general sense. These issues obviously make it difficult to construct adequate measurement instruments.
The paper seeks to achieve three goals: 1) to review existing approaches and highlight their weak points; 2) to propose a theoretical framework for analyzing governmental effectiveness using appropriate estimation tools; and 3) to present empirical results based on data on public health care from Russia’s regions. Three patterns that ought to correlate - regional efficiency, how reform has been implemented and public opinion – are, instead, inconsistent with each other. Russia’s health-care sector today faces considerable problems with basic, systemic effectiveness.
Over the past decade Russia has experienced stable economic growth with Gross Domestic Product (GDP) growing by 7 percent per year from 1998 to 2007. While the nation still enjoys a relatively healthy growth rate, analysis shows that the sources for the future growth are limited and to boost growth Russia should rely on increasing labor productivity. Improving productivity will impose new demands on Russia's workforce requiring better skills to satisfy the needs of economy growth. The international business environment survey reports that Russia's private sector considers the lack of skills and education of workers to be the most severe constraint on its expansion and growth. Despite the very high level of formal education attained by Russian workers the problem behind this may be explained by the current quality and content of education, which does not develop the necessary skills and competences demanded by the labor market. This report examines the reasons and the consequences of this skills deficit, which constrain productivity and limits innovation ultimately stifling accelerated economic growth in Russia. The objectives of the report are: 1) to deepen the understanding of the structure and composition of this skills deficit by analyzing in detail the demand for and supply of particular cognitive and non-cognitive skills; 2) to review the capacity and problems of the current systems for skills provision in Russia both through the public and private provision thereby identifying some of the underlying reasons for this skills gap; and 3) to support the development of evidence-based policy making in professional education and training, which will lead to a system better responding to the challenges of the economy and labor market.
In this paper, we consider the following problem - what affects the amount of investment in knowledge when one of the network firms enters another innovation network. The solution of this problem will allow us to understand exactly how innovative companies will behave when deciding whether to enter the innovation network of another country or region, what conditions affect it and how the level of future investments in knowledge can be predicted.
This article studies the relationship between exporting and past productivity at the firm level. Panel data from two surveys of Russian manufacturing firms conducted in 2005 and 2009 are used. We analyse the difference between continuing and new exporters, and study how drivers to exporting differ if firms export to CIS or high-wage advanced countries. We find empirical evidence for the self-selection hypothesis: both continuing and new exporters are more productive and larger than non-exporters and export quitters. Path dependence in the nature of foreign trade ceased to exist: serving the markets of the former Soviet Union requires the same productivity advantage as exporting to the developed countries.
Over the past decade Russia has experienced stable economic growth with Gross Domestic Product (GDP) growing by 7 percent per year from 1998 to 2007. While the nation still enjoys a relatively healthy growth rate, analysis shows that the sources for the future growth are limited and to boost growth Russia should rely on increasing labor productivity. Improving productivity will impose new demands on Russia's workforce requiring better skills to satisfy the needs of economy growth. The international business environment survey reports that Russia's private sector considers the lack of skills and education of workers to be the most severe constraint on its expansion and growth. Despite the very high level of formal education attained by Russian workers the problem behind this may be explained by the current quality and content of education, which does not develop the necessary skills and competences demanded by the labor market. This report examines the reasons and the consequences of this skills deficit, which constrain productivity and limits innovation ultimately stifling accelerated economic growth in Russia. The objectives of the report are: 1) to deepen the understanding of the structure and composition of this skills deficit by analyzing in detail the demand for and supply of particular cognitive and non-cognitive skills; 2) to review the capacity and problems of the current systems for skills provision in Russia both through the public and private provision thereby identifying some of the underlying reasons for this skills gap; and 3) to support the development of evidence-based policy making in professional education and training, which will lead to a system better responding to the challenges of the economy and labor market.
DEA-analysis is performed based on publicly available data on 94 world largest fashion retailers. Standard clusterization of coefficients obtained from DEA-analysis gives clusters that are analyzed with respect to homogeneity and fit to the types of strategic behavior outlined in strategic management.
Once the legacy of the global financial crisis has been overcome, global GDP could grow at around 3% per year over the next 50 years. Growth will be enabled by continued fiscal and structural reforms and sustained by the rising share of relatively fast-growing emerging countries in global output. Growth of the non-OECD will continue to outpace the OECD, but the difference will narrow over coming decades. From over 7% per year over the last decade, non-OECD growth will decline to around 5% in the 2020s and to about half that by the 2050s, whereas trend growth for the OECD will be around on average 1¾ to 2¼% per year. The next 50 years will see major changes in the relative size of world economies. Fast growth in China and India will make their combined GDP measured at 2005 Purchasing Power Parities (PPPs), soon surpass that of the G7 economies and exceed that of the entire current OECD membership by 2060. Notwithstanding fast growth in low-income and emerging countries, large cross-country differences in living standards will persist in 2060. Income per capita in the poorest economies will more than quadruple by 2060, and China and India will experience more than a seven-fold increase, but living standards in these countries and some other emerging countries will still only be one-quarter to 60% of the level in the leading countries in 2060. In the absence of more ambitious policy changes, rising imbalances could undermine growth. As the current cycle unwinds, the scale of global current account imbalances may increase and return to pre-crisis peaks by 2030. Government indebtedness among many OECD countries will exceed thresholds at which there is evidence of adverse effects on interest rates and growth. Global interest rates may therefore start to rise over the long-term. Bolder structural reforms and more ambitious fiscal policy could raise long-run living standards by an average of 16% relative to the baseline scenario of moderate policy improvements. Ambitious product market reforms, which raise productivity growth, could increase global GDP by an average of about 10%. Policies that induce convergence towards best practice labour force participation could increase GDP by close to 6% on average.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.