Polish EU accession in comparative perspective:macroeconomics, finance and the government

This book is a collection of papers that focusses on the macroeconomic and financial aspects of EU accession of its largest new member, Poland, seen in comparative perspective. Two main themes are covered. One relates to empirical estimations, evaluating the effects of integration on fiscal balance, prices, seigniorage wealth and FDI flows. The second theme relates to institutional reform and policy recommendations. Discussion focuses on how transparency and fiscal rules, including those implied by EU accession, may help to reduce the deficit bias in fiscal policy; what is the institutional framework for low inflation and how to make the insurance sector regulation more efficient, including its implications for insurance offer for small and medium-size enterprises. Last but not least, the Irish model of development and the role of the foreign direct investment in it is discussed, including the applicability of the Irish policy in Poland and other new EU member states.

Foreign and domestic investment:regional development or crowding out?

This paper tests, at the regional and industry level, the extent to which domestic investment is stimulated or crowded out by inward foreign direct investment. The paper develops a model of domestic investment, based on standard models drawn from macroeconomics and industrial economics. The paper then goes on to show that, at a general level, the 'development' or agglomeration hypothesis is confirmed that domestic investment is indeed stimulated by inward investment. However, there is also evidence that, in certain regions, inward investment has crowded out domestic investment. The implications of this from the perspective of regional policy are briefly discussed.

Credit and collateral

Collateral - generally defined as an asset used to provide security for a lender's loan - is an important feature of credit contracts and all the available evidence suggests that its use is getting more pervasive. This informative book builds upon recent research into this topic. Sena analyses three case-studies that revolve around the impact that financial constraints have on economic outcomes. In the first case-study, the relationship between firms' technical efficiency and increasing financial pressure is explored. The author then goes on to show, in the second case study, that under specific circumstances, increasing financial pressure and increasing product market competition can jointly have a positive impact on firms' technical efficiency, while not being true for all types of firms. In the third case, she analyses the impact that finance constraints have on women's start-ups. Unique and revealing, this is the first book to deal so extensively with the topic of collateral, and as such, is a valuable reference to postgraduates and professionals in the fields of macroeconomics, monetary and business economics. © 2008 Vania Sena. All rights reserved.

Does money matter in inflation forecasting

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation.

Innovation, intellectual property and economic growth

What drives innovation? How does it contribute to the growth of firms, industries, and economies? And do intellectual property rights help or hurt innovation and growth? Uniquely combining microeconomics, macroeconomics, and theory with empirical analysis drawn from the United States and Europe, this book introduces graduate students and advanced undergraduates to the complex process of innovation. By addressing all the major dimensions of innovation in a single text, Christine Greenhalgh and Mark Rogers are able to show how outcomes at the microlevel feed through to the macro-outcomes that in turn determine personal incomes and job opportunities. In four sections, this textbook comprehensively addresses the nature of innovation and intellectual property, the microeconomics and macroeconomics of innovation, and economic policy at the firm and macroeconomic levels. Among the topics fully explored are the role of intellectual property in creating incentives to innovate; the social returns of innovation; the creation and destruction of jobs by innovation; whether more or fewer intellectual property rights would give firms better incentives to innovate; and the contentious issues surrounding international treaties on intellectual property.

Why are aggregate equity payouts pro-cyclical?

We use two general equilibrium models to explain why changes in the external economic environment result in pro-cyclical aggregate dividend payout behavior. Both models that we consider endogenize low elasticity of investment. The first model incorporates capital adjustment costs, while the second one assumes that risk-averse managers maximize their own objective function rather than shareholder wealth. We show that, while both models generate pro-cyclical aggregate dividends, a feature consistent with the observed business-cycle pattern of payouts from well-diversified portfolios, the second model provides a more likely explanation for this effect. Our findings emphasize the importance of incorporating agency conflicts when considering the relationship between the external economic environment and the financial behavior of businesses.

Does money matter in inflation forecasting?

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two nonlinear techniques, namely, recurrent neural networks and kernel recursive least squares regressiontechniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a nave random walk model. The best models were nonlinear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. Beyond its economic findings, our study is in the tradition of physicists' long-standing interest in the interconnections among statistical mechanics, neural networks, and related nonparametric statistical methods, and suggests potential avenues of extension for such studies. © 2010 Elsevier B.V. All rights reserved.