Economics

In the Grossman and Helpman (1994) model of endogenous trade protection, sectoral lobbies try to influence an incumbent government that maximizes a weighted sum of political contributions and aggregate welfare. We empirically investigate this model using US and Turkish data. Our specification is more tightly tied to theory than those in existing studies. Additionally, we assume all specific-factor owners to be organized into different lobbies.

In this paper, we empirically analyze the effects of trade reforms on import demand and derive their implications on economic development in Turkey, a country that underwent sudden and substantial trade liberalization in the mid-1980s. The tool for this analysis is the estimation of disaggregated import demand elasticities. The adoption of a more liberal trade regime as well as radical attempts to foster economic development makes the Turkish experience particularly interesting for analysis. Almost all of our elasticities are estimated to be significant, unlike those of most previous studies in the literature on other countries. We test for different elasticities over "closed" and "open" economy periods, and find that the effects of the trade reforms of the 1980s were significant for a number of industries that form the backbone of the Turkish economy. We also compare our results with elasticity estimates from past studies for developed countries.

Using singular spectrum analysis (SSA), we model the realized volatility and logarithmic standard deviations of two important futures return series. The realized volatility and logarithmic standard deviations are constructed following the methodology of Andersen et al. [J. Am. Stat. Ass. 96 -55] using intra-day transaction data. We ÿnd that SSA decomposes the volatility series quite well and e ectively captures both the market trend (accounting for about 34 -38% of the total variance in the series) and, more importantly, a number of underlying market periodicities. Reliable identiÿcation of any periodicities is extremely important for options pricing and risk management and we believe that SSA can be a useful addition to the ÿnancial practitioners' toolbox.

We examine the forecasting performance of a number of parametric and nonparametric models based on a training-validation sample approach and the use of rolling short-term forecasts to compute root mean-squared errors. We find that the performance of these models is better than that of the naïve, no-change model. The use of bivariate models (like VAR and transfer functions) provides additional root mean-squared error reductions. In many cases the nonparametric models forecast as well or better than the parametric models. Our analysis suggests that (a) nonparametric models are attractive complements to parametric univariate models, and (b) simple VAR models should be considered before attempting to fit transfer function models. * We would like to thank Clive Granger, Rick Ashley and Victor Zarnowitz for very useful discussions and suggestions and three anonymous referees for detailed comments. We would also like to thank Rick Ashley for providing us with the test results for the bootstrap-based forecast evaluation test and very useful discussions. Any remaining errors are our responsibility. He has done research on the small sample properties of VAR cointegration test statistics, on structural macroeconomic models and on forecasting currency crises. His current research focuses on the relative forecasting performance of structural econometric, time series and nonparametric models. He has previously published in the He has published several articles on the efficiency of combining time series forecasts and analysts' forecasts of corporate earnings, the time series behavior of mergers, optimization and strategic planning, the financing of R&D, and executive compensation, His articles have appeared in the

Using Turkish industry-level data from 1983 to 1990, we find that politically organized industries receive both higher protection and promotion than unorganized ones. Tariff rates are decreasing (increasing) in the import-penetration ratio and the absolute value of the importdemand elasticity for organized (unorganized) industries. Subsidy rates are decreasing (increasing) in the output-supply elasticity for organized (unorganized) industries. The results are consistent with the predictions of the Grossman-Helpman model and its extension in this paper. The mix of protection and promotion is inversely related to the ratio of their respective marginal deadweight cost measures.

Using exchange rate uncertainty (ERU) and sociopolitical instability (SPI) as measures of macroeconomic imbalances and political disorder, respectively, we investigate the link between these two factors and private investment in Latin America. The analysis shows that while ERU and SPI negatively impact private investment jointly, the individual impact of ERU is much greater than that of SPI. Our results should prove useful both to policymakers and others interested in understanding the impact of uncertainty on private investment. Most importantly, macroeconomic policies that limit excess volatility in relative prices should lessen an economy's general level of investment risk leading to enhanced private investment. Further, though lesser in degree, institutional reforms that reduce social tensions and strengthen property rights should also stimulate private investment. Finally, structural reforms that combine these two are likely to foster a robust market for private investment thus contributing to an economy's growth potential. . For helpful comments, we would like to thank Charles Register and session participants of the Latin America Econometric Society Meetings, and LACEA Meetings. We would also like to thank an anonymous referee for constructive criticism that substantially improved the content and presentation of the paper. The usual disclaimer applies.

We extend earlier work on the NoVaS transformation approach introduced by Politis (2003a,b). The proposed approach is model-free and especially relevant when making forecasts in the context of model uncertainty and structural breaks. We introduce a new implied distribution in the context of NoVaS , a number of additional methods for implementing NoVaS and we examine the relative forecasting performance of NoVaS for making volatility predictions using real and simulated time series. We pay particular attention to data generating processes with varying coefficients and structural breaks. Our results clearly indicate that the NoVaS approach outperforms GARCH-made forecasts models in all cases we examined, except (as expected) when the data generating process was itself a GARCH model.

In this paper, we explore the extent of exchange rate pass-through for the USA, UK and Japan using a post-Bretton Woods industry-level dataset. We then investigate how di®erent channels of exchange rate pass-through a®ect domestic and import prices. Our analysis is suggestive of two channels of transmission and we¯nd considerable variation in the extent of pass-through across industries and countries.

We examine whether industry-level forecasts of CPI and PPI inflation can be improved when we use the "exchange rate pass-through" effect, that is, when we account for the variability of the exchange rate and import prices. We build a forecasting model based on a two or three equation system involving CPI and PPI inflation where the effects of the exchange rate and import prices are explicitly taken into account. This setup also incorporates their dynamics, lagged correlations and appropriate restrictions suggested by economic theory. We compare the forecasting performance of our model with a variety of unrestricted univariate, multivariate time series models with and without standard control variables for inflation, like interest rates and unemployment. Our results suggest that improvements on the forecast accuracy can be effected when one takes into account the possible pass-through effects of exchange rates and import prices on CPI and PPI inflation.

We build on extant theory of the MNC, MNC subsidiaries, absorptive capacity and Penrose's concept of 'productive opportunity' to develop a framework on the MNC and absorptive capacity (AC) that allows us to explore the role of subsidiaries in the global sourcing of knowledge. We develop and test hypotheses using primary questionnaire-collected data. Our results support the idea that subsidiaries' realized AC can be improved by the realized and potential AC of the MNC group and the subsidiary and in turn may improve the performance of the subsidiaries and the group as a whole.

In this paper I propose a novel optimal linear filter for smoothing, trend and signal extraction for time series with a unit root. The filter is based on the Singular Spectrum Analysis (SSA) methodology, takes the form of a particular moving average and is different from other linear filters that have been used in the existing literature. To best of my knowledge this is the first time that moving average smoothing is given an optimality justification for use with unit root processes. The frequency response function of the filter is examined and a new method for selecting the degree of smoothing is suggested. I also show that the filter can be used for successfully extracting a unit root signal from stationary noise. The proposed methodology can be extended to also deal with two cointegrated series and I show how to estimate the cointegrating coefficient using SSA and how to extract the common stochastic trend component. A simulation study explores some of the characteristics of the filter for signal extraction, trend prediction and cointegration estimation for univariate and bivariate series. The practical usefulness of the method is illustrated using data for the US real GDP and two financial time series.

Using a newly developed dataset of daily, value-weighted market returns we construct and analyze the monthly realized volatility of the Athens Stock Exchange (A.S.E.) from 1985 to 2003. Our analysis focuses on the distributional and time series properties of the realized volatility series and on assessing the connection between realized volatility and returns through a multi-factor asset pricing model. In particular, we find strong evidence on the existence of a volatility feedback effect and a leverage effect, and on the existence of asymmetries between lagged returns and volatility. Furthermore, we examine the cross-sectional distribution of unconditional loadings on the realized risk factor(s) for different sets of characteristics-sorted common stock portfolios. We find that realized risk is a significantly priced factor in A.S.E. and its high explanatory power for the cross-section of portfolio average returns is independent of any return variation related to the market (CAPM) or size and book-to-market (Fama-French) factors. We discuss our findings in the context of the recent literature on realized volatility and feedback effects, as well as the literature on the pricing power of realized risk (JEL: G12)

This paper explores the connection between inflation and its higher-order moments in the case of the Spanish economy from 1975 to 1999. We found evidence of a strong positive correlation between aggregate inflation and the distribution of relative-change prices. Also, a standard Phillips curve is used to study aggregate supply shocks. The results strongly support our model from 1975 onwards and we are able to document, for the first time, the dynamic features of the relative-price adjustment process. Small sample problems are addressed.

The effects of scheduled macroeconomic announcements on the real-time intraday return volatilities, covariances, and correlations between the Eurodollar futures and the U.S. Treasury bond futures markets are studied. These announcements are responsible for most of the observed intraday jumps in 816 Thomakos, Wang, Wu, and Chuderewicz

We propose structural models of investment for the econometric estimation of the real option markup. Count data models offer flexible specifications for bringing real option investment models to aggregate market data. The empirical results for oil tanker investment data are supportive for the proposed structural models, as well as the real option hypothesis. We find that the sensitivity of investment to the real option rule is much higher than expected. Finally, this framework may be applied for any industry and provides a "trading volume" model for investment activity.

In this paper, we investigate the informational content of retained and distributed earnings for future profitability and market mispricing. We find that there are systematic differences in the persistence among the components of retained earnings (current operating accruals, non current operating accruals and retained cash flows) and between the components of distributed earnings (cash flows distributed to debtholders and equityholders). Moreover, the overall sustainability of retained earnings is less than that of distributed earnings. This result holds, despite the lower persistence of retained cash flows relative to cash flows distributed to debtholders. In addition, we show that investors do not distinguish and similarly overestimate the different implications of each component of retained earnings for future profitability.