Boriss Siliverstovs

Convergence of European spot market prices for natural gas? A real-time analysis of market integration using the Kalman Filter

This letter provides a textbook example of an econometric analysis of the integration between two commodity markets and the subsequent price convergence or absence thereof. Price relations between spot markets are analysed for natural gas in Europe. The European market for natural gas is currently undergoing a liberalization process with the aim of creating a single, unified market. Time-varying coefficient estimation models are used, applying the Kalman filter to test whether price convergence between different locations is really taking place. The results reveal that the construction of a pipeline between the UK and Zeebrugge (Belgium) has led to almost perfect price convergence between these locations in the time period under consideration; on the other hand, liberalization on the European continent does not seem to be working so far.

Export-led growth hypothesis: evidence for Chile

This study examines the export-led growth hypothesis using annual time series data from Chile. It addresses the problem of specification bias under which previous studies have suffered and focuses on the impact of manufactured and primary exports on the economic growth. In order to investigate if and how manufactured and primary exports affect economic growth via increases in productivity, the study uses the Toda and Yamamoto (1995) procedure for testing for Granger non-causality in Vector Autoregressive models that involve variables that are integrated in an arbitrary order and that are possibly cointegrated. The estimation results support the export-led growth hypothesis for Chile and at the same time point out to the differentiated impact of manufactured and primary exports on the economic growth.

On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence

Summary In this paper we perform a comparative study of the forecasting properties of the about 30 alternative leading indicators for Germany using the growth rates of German real GDP. In addition to them, we have constructed a diffusion index based on the principal component analysis and including 145 component series that reflect all the facets of German economy. We use the post-unification data which cover years from 1991 through 2004. Using a battery of statistical tests we detect a structural break in the growth rates that occurs in the first half of 2001. Our results suggest that the forecasting ability of the leading indicators has been rather good in the pre-break period with our diffusion index showing the superior forecasting accuracy but the forecasting performance of all alternative indicators has significantly deteriorated in the post-break period, i.e. in 2001-2004. None of the leading indicator models was able to predict and accommodate the structural break in the growth rates of the time series under scrutiny. This finding confirms the widespread impression among the practitioners that the state of German economy in the recent years became much more difficult to forecast.

A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder

Abstract In this paper, we make multi-step forecasts of the annual growth rates of the real GDP for each of the 16 German Länder simultaneously. We apply dynamic panel models accounting for spatial dependence between regional GDP. We find that both pooling and accounting for spatial effects help to improve the forecast performance substantially. We demonstrate that the effect of accounting for spatial dependence is more pronounced for longer forecasting horizons (the forecast accuracy gain is about 9% for a 1-year horizon and exceeds 40% for a 5-year horizon). We recommend incorporating a spatial dependence structure into regional forecasting models, especially when long-term forecasts are made.

Climate change and modelling of extreme temperatures in Switzerland

This study models maximum temperatures in Switzerland monitored in twelve locations using the generalised extreme value (GEV) distribution. The parameters of the GEV distribution are determined within a Bayesian framework. We find that the parameters of the underlying distribution underwent a substantial change in the beginning of the 1980s. This change is characterised by an increase both in the level and the variability. We assess the likelihood of the heat wave of the summer 2003 using the fitted GEV distribution by accounting for the presence of a structural break. The estimation results do suggest that the heat wave of 2003 is not that statistically improbable if an appropriate methodology is used for dealing with nonstationarity.

Manufacturing exports, mining exports and growth: cointegration and causality analysis for Chile (1960-2001)

This study examines the export-led growth hypothesis using annual time series data from Chile in a production function framework. It addresses the problem of specification bias under which previous studies have suffered, and focuses on the impact of manufactured and mining exports on productivity growth. In order to investigate if and how manufactured and mining exports affect economic growth via increases in productivity, the study uses Johansen cointegration technique. The estimation results can be interpreted as evidence of productivity-enhancing effects of manufactured exports and of productivity-limiting effects of mining exports.

What Drives Housing Prices Down? Evidence from an International Panel

Summary In this study, we suggest an explanation for the low growth rates of real housing prices in Canada and Germany in comparison to other OECD countries over the period 1975-2005. We show that the long-run development of housing markets is determined by real disposable per-capita income, the real long-term interest rate, population growth, and urbanization. The differential development of real housing prices in Canada and Germany is attributed to the fundamentals in these two countries. Canada and Germany are characterized by relatively low average growth rates of real disposable income and relatively high interest rates, resulting in depressed housing prices over a long period of time. Institutional structure accentuates these tendencies. Given the importance of housing wealth for private consumption, our paper aims at drawing the attention of policymakers to the necessity of preventing not only overheating but also overcooling of the housing market that entails lower economic growth rate.

The Russian Regional Convergence Process: Where Does It Go?

This paper investigates the income convergence among Russian regions in the period 1998-2006. It makes two major contributions to rather extensive literature on the regional convergence in Russia. First, it identifies spatial regimes using the exploratory spatial data analysis. Second, it examines the impact of spatial effects on the convergence process. Our results show that the overall speed of regional convergence in Russia, being low by international standards, becomes even lower after controlling for spatial effects. However, when accounting for the spatial regimes, we find a strong regional convergence among high-income regions located near other high-income regions. Our results indicate that estimation of speed of convergence using aggregate data may result in misleading conclusions regarding the nature of convergence process among Russias regions.

Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland

This study utilizes the dynamic factor model of Giannone et al. (2008) in order to make now-/forecasts of GDP quarter-on-quarter growth rates in Switzerland. It also assesses the informational content of macroeconomic data releases for forecasting of the Swiss GDP. We find that the factor model offers a substantial improvement in forecast accuracy of GDP growth rates compared to a benchmark naive constant-growth model at all forecast horizons and at all data vintages. The largest forecast accuracy is achieved when GDP nowcasts for an actual quarter are made about three months ahead of the official data release. We also document that both business tendency surveys as well as stock market indices possess the largest informational content for GDP forecasting although their ranking depends on the underlying transformation of monthly indicators from which the common factors are extracted.

Banking Competition, Good or Bad?: The Case of Promoting Micro and Small Enterprise Finance in Kazakhstan

Competition is claimed to be beneficial in development projects promoting micro and small enterprise finance although there are still doubts as to whether these loans can be developed into a profitable business. Our research sheds new light on the question of how many MSE banking units should optimally be created and supported in a certain region. We employ a unique data set from the European Bank for Reconstruction and Development for Kazakhstan, and investigate which strategy contributes more to the overall success of the programme: a strategy of setting up several competing banks or a strategy of establishing regional monopolies. ‘Competition is the most important principle on which our strategy is based. As in any other market, effective competition provides incentives for banks to offer market-based and demand-oriented financial services. Competition encourages the development of better products and services at lower cost.’ (Matthäus-Maier and von Pischke, 2004, p. 1).