Financial Factors in Macroeconometric Models
Sebastian Giesen
Volkswirtschaft, Ökonomie, Shaker Verlag GmbH, Aachen,
2013
Abstract
The important role of credit has long been identified as a key factor for economic development (see e.g. Wicksell (1898), Keynes (1931), Fisher (1933) and Minsky (1957, 1964)). Even before the financial crisis most researchers and policy makers agreed that financial frictions play an important role for business cycles and that financial turmoils can result in severe economic downturns (see e.g. Mishkin (1978), Bernanke (1981, 1983), Diamond (1984), Calomiris (1993) and Bernanke and Gertler (1995)). However, in practice researchers and policy makers mostly used simplified models for forecasting and simulation purposes. They often neglected the impact of financial frictions and emphasized other non financial market frictions when analyzing business cycle fluctuations (prominent exceptions include Kiyotaki and Moore (1997), Bernanke, Gertler, and Gilchrist (1999) and Christiano, Motto, and Rostagno (2010)). This has been due to the fact that most economic downturns did not seem to be closely related to financial market failures (see Eichenbaum (2011)). The outbreak of the subprime crises ― which caused panic in financial markets and led to the default of Lehman Brothers in September 2008 ― then led to a reconsideration of such macroeconomic frameworks (see Caballero (2010) and Trichet (2011)). To address the economic debate from a new perspective, it is therefore necessary to integrate the relevant frictions which help to explain what we have experienced during recent years.
In this thesis, I analyze different ways to incorporate relevant frictions and financial variables in macroeconometric models. I discuss the potential consequences for standard statistical inference and macroeconomic policy. I cover three different aspects in this work. Each aspect presents an idea in a self-contained unit. The following paragraphs present more detail on the main topics covered.
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Natural-resource or Market-seeking FDI in Russia? An Empirical Study of Locational Factors Affecting the Regional Distribution of FDI Entries
K. Gonchar, Philipp Marek
HSE Working Papers, Series: Economics, WP BRP 26/EC/2013,
2013
Abstract
This paper analyzes the spatial distribution of foreign direct investment (FDI) across regions in Russia. Our analysis employs data on Russian firms with a foreign investor during the 2000-2009 period and links regional statistics in the conditional logit model. The main findings are threefold. First, we conclude that market-related factors and the availability of natural resources are important factors in attracting FDI. Second, existing agglomeration economies encourage foreign investors. Third, the findings imply that service-oriented FDI co-locates with extraction industries in resource-endowed regions.
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Has the Euro Increased International Price Elasticities?
Oliver Holtemöller, Götz Zeddies
Empirica,
No. 1,
2013
Abstract
The introduction of the Euro has been accompanied by the hope that international competition between EMU member states would increase due to higher price transparency. This paper contributes to the literature by analyzing price elasticities in international trade flows between Germany and France and between Germany and the United Kingdom before and after the introduction of the Euro. Using disaggregated Eurostat trade statistics, we adopt a heterogeneous dynamic panel framework for the estimation of price elasticities. We suggest a Kalman-filter approach to control for unobservable quality changes which otherwise would bias estimates of price elasticities. We divide the complete sample, which ranges from 1995 to 2008, into two sub-samples and show that price elasticities in trade between EMU members did not change substantially after the introduction of the Euro. Hence, we do not find evidence for an increase in international price competition resulting from EMU.
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Natural-resource or Market-seeking FDI in Russia? An Empirical Study of Locational Factors Affecting the Regional Distribution of FDI Entries
K. Gonchar, Philipp Marek
IWH Discussion Papers,
No. 3,
2013
Abstract
This paper conducts an empirical study of the factors that affect the spatial distribution of foreign direct investment (FDI) across regions in Russia; in particular, this paper is concerned with those regions that are endowed with natural resources and market-related benefits. Our analysis employs data on Russian firms with a foreign investor during the 2000-2009 period and linked regional statistics in the conditional logit model. The main findings are threefold. First, we conclude that one theory alone is not able to explain the geographical pattern of foreign investments in Russia. A combination of determinants is at work; market-related factors and the availability of natural resources are important factors in attracting FDI. The relative importance of natural resources seems to grow over time, despite shocks associated with events such as the Yukos trial. Second, existing agglomeration economies encourage foreign investors by means of forces generated simultaneously by sector-specific and inter-sectoral externalities. Third, the findings imply that service-oriented FDI co-locates with extraction industries in resource-endowed regions. The results are robust when Moscow is excluded and for subsamples including only Greenfield investments or both Greenfield investments and mergers and acquisitions (M&A).
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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Journal of International Money and Finance,
No. 35,
2013
Abstract
The signals approach as an early-warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it cannot distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful results; (2) that composite indicators aggregating information contained in individual indicators add value to the signals approach; and (3) that indicators which are found to be significant in-sample usually perform similarly well out-of-sample.
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The Structural Determinants of the US Competitiveness in the Last Decades: A 'Trade-Revealing' Analysis
Massimo Del Gatto, Filippo di Mauro, Joseph Gruber, Benjamin Mandel
ECB Working Paper,
No. 1443,
2012
Abstract
We analyze the decline in the U.S. share of world merchandise exports against the backdrop of a model-based measure of competitiveness. We preliminarily use constant market share analysis and gravity estimations to show that the majority of the decline in export shares can be associated with a declining share of world income, suggesting that the dismal performance of the U.S. market share is not a sufficient statistic for competitiveness. We then derive a computable measure of country-sector specific real marginal costs (i.e. competitiveness) which, insofar it is inferred from actual trade ows, is referred to as 'revealed'. Brought to the data, this measure reveals that most U.S. manufacturing industries are losing momentum relative to their main competitors, as we find U.S. revealed marginal costs to grow by more than 38% on average. At the sectoral level, the "Machinery" industry is the most critical.
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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Abstract
The signals approach as an early warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it does not distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful and statistically significant results and (2) that composite
indicators aggregating information contained in individual indicators add value to the signals approach, even where most individual indicators are not statistically significant on their own.
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Towards Unrestricted Public Use Business Microdata: The Synthetic Longitudinal Business Database
John M. Abowd, Ron S. Jarmin, Satkartar K. Kinney, Javier Miranda, Jerome P. Reiter, Arnold P. Reznek
International Statistical Review,
No. 3,
2011
Abstract
In most countries, national statistical agencies do not release establishment-level business microdata, because doing so represents too large a risk to establishments’ confidentiality. One approach with the potential for overcoming these risks is to release synthetic data; that is, the released establishment data are simulated from statistical models designed to mimic the distributions of the underlying real microdata. In this article, we describe an application of this strategy to create a public use file for the Longitudinal Business Database, an annual economic census of establishments in the United States comprising more than 20 million records dating back to 1976. The U.S. Bureau of the Census and the Internal Revenue Service recently approved the release of these synthetic microdata for public use, making the synthetic Longitudinal Business Database the first-ever business microdata set publicly released in the United States. We describe how we created the synthetic data, evaluated analytical validity, and assessed disclosure risk.
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Government Banking in Russia: Magnitude and New Features
Andrei Vernikov
IWH Discussion Papers,
No. 13,
2011
Abstract
State-controlled banks are currently at the core of financial intermediation in Russia. This paper aims to assess the magnitude of government banking, and to reveal some of its special features and arrangements. We distinguish between directly and indirectly state-controlled banks and construct a set of bank-level statistical data covering the period between 2000 and 2011. By January 2011 the market share of state-controlled banks reached almost 54 percent of all bank assets, putting Russia in the same league with China and India and widening the gap from typical European emerging markets. We show that direct state ownership is gradually substituted by indirect ownership and control. It tends to be organized in corporate pyramids that dilute public property, take control away from government bodies, and underpin managerial opportunism. Statecontrolled
banks blur the borderline between commercial banking and development
banking. Dominance of public banks has a bearing on empirical studies whose results might suggest state-owned banks’ greater (or lesser) efficiency or competitiveness compared to other forms of ownership. We tend to interpret such results as influenced by the choice of indicator, period of observations, sample selection, etc., in the absence of an equal playing field for all groups of players. We suggest that the government’s planned retreat from the banking sector will involve non-core assets mainly, whereas control over core institutions will just become more subtle.
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The Revealed Competitiveness of U.S. Exports
Massimo Del Gatto, Filippo di Mauro, Joseph Gruber, Benjamin Mandel
Federal Reserve Discussion Paper,
No. 1026,
2011
Abstract
The U.S. share of world merchandise exports has declined sharply over the last decade. Using data at the level of detailed industries, this paper analyzes the decline in U.S. share against the backdrop of alternative measures of the competitiveness of the U.S. economy. We document the following facts: (i) only a few industries contributed to the decline in any meaningful way, (ii) a large part of the drop was driven by the changing size of U.S. export industries and not the size of U.S. sales within those industries, (iii) in a gravity framework, the majority of the decline in the U.S. export share within industries was due to the declining U.S. share of world income, and (iv) in a computed structural measure of firm productivity, average U.S. export productivity has generally maintained its high level versus other countries over time. Overall, our analysis suggests that the dismal performance of the U.S. market share is not a sufficient statistic for competitiveness.
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