Empirical Economics

For many economic time-series variables that are observed regularly and frequently, for example weekly, the underlying activity is not distributed uniformly across the year. For the aim of predicting annual data, one may consider temporal aggregation into larger subannual units based on an activity timescale instead of calendar time. Such a scheme may strike a balance between annual modeling (which processes little information) and modeling at the finest available frequency (which may lead to an excessive parameter dimension), and it may also outperform modeling calendar time units (with some months or quarters containing more information than others). We suggest an algorithm that performs an approximate inversion of the inherent seasonal time deformation. We illustrate the procedure using two exemplary weekly time series.

Exportation nowadays has a crucial role on economies in all around the world. Like other developing countries, there have been remarkable studies and attempts specifically in Turkish economy. To reveal this conclusion more, we deal with the issue of how to develop Turkish economy. In this way, firstly, we try to explain the concept export diversification and then, apply it to Turkish exportation. That's why, we show the ways how export diversification effects economic growth in Turkey positively. Through this effort, it has been conceived that export diversification has generally an important role, especially for economic growth. Second, we claim that the most important actors in economic growth are Gross Domestic Product (GDP) and Gross National Product (GNP). To present this idea, we explain some economic terms such as Export, Export Diversification, Economy, Economic Growth, Gross Domestic Product (GDP) and Gross National Product (GNP). The main target of the essay is to find out how to develop Turkish economy.

This paper explores the mean-reverting behavior of the unemployment rate using monthly geographically disaggregated data for the period 1991:01 through 2012:02. We apply both standard unit-root tests and tests that allow for one and two structural breaks in the mean. We find evidence that favors both unit-root and stationary processes. No series exhibits stationarity around a constant mean, which does not support the traditional natural-rate hypothesis, but about half of the series exhibit stationarity around a shifting mean. For these series, we find that the break occurs at the Great Recession. To complement the unit-root analysis, we also examine the behavior of the series using the Bai and Perron methods to detect multiple regimes at unknown points of time. We find that the Great Recession also altered the persistence of the unemployment rate series over the identified regimes. In general, the values of the estimated persistence within regimes decrease between those regimes, implying faster absorption of shocks later in the sample period.

This paper explores the mean-reverting behavior of the unemployment rate using monthly geographically disaggregated data for the period 1991:01 through 2012:02. We apply both standard unit-root tests and tests that allow for one and two structural breaks in the mean. We find evidence that favors both unit-root and stationary processes. No series exhibits stationarity around a constant mean, which does not support the traditional natural-rate hypothesis, but about half of the series exhibit stationarity around a shifting mean. For these series, we find that the break occurs at the Great Recession. To complement the unit-root analysis, we also examine the behavior of the series using the Bai and Perron methods to detect multiple regimes at unknown points of time. We find that the Great Recession also altered the persistence of the unemployment rate series over the identified regimes. In general, the values of the estimated persistence within regimes decrease between those regimes, implying faster absorption of shocks later in the sample period.

This paper aims to investigate the effects of macroeconomic variables on stock market volatility in three Asian countries by applying GARCH MIDAS model. The study covers the period from 01/2003 to 06/2014. The GARCH MIDAS framework allows to incorporate macro variables directly in the model and obtain long-term and short-term volatility separately. Empirical findings show that some macroeconomic variables significantly affect stock market volatility. While Chinese and South Korean stock market reacts to either inflation or industrial production growth information, Japanese stock market is sensitive to both factors. In addition, macroeconomic factors influence three markets at different magnitude. The results also indicate that three markets behave differently to the same factors. Real oil price shock stems from aggregate demand significantly lowers Japanese stock market volatility. In contrast, South Korean and Chinese stock market volatility is positively influenced by the same sho...

Seasonal cointegration generalizes the idea ofcointegration to processes with unit roots at frequencies different from 0. Here, "common seasonals," also a dual notion of common trends, is adopted for the seasonal case. The features are demonstrated in exemplary models for German and U.K. data. An evaluation of the predictive value of accounting for seasonal cointegration shows that seasonal cointegration may be difficult to exploit to improve predictive accuracy even in cases where seasonal non-cointegration is clearly rejected on statistical grounds. The findings from the real-world examples are corroborated by Monte Carlo simulation.

This article investigates the effects and transmission channels of shocks between two asymmetric neighboring countries. In particular, we investigate Austria and Germany which are highly integrated due to their common language and common membership of the European Monetary Union. Generalized impulse response functions reveal that there are large and significant effects of shocks to the German economy on Austria. In contrast, the effects of shocks to the Austrian economy on Germany are barely significant and if they are, their magnitude is comparatively small. Furthermore we can show that multiplier effects are present in Germany but not in Austria and we identify hysteretic properties in Austrian unemployment.

The COVID-19 pandemics and the lockdowns imposed to mitigate the rise of infections beyond manageable levels strongly affected international trade. Although the health crisis and the mobility restrictions associated with lockdowns are closely related, their impacts on international trade have a different nature. This paper uses monthly firm-level trade data for Portuguese firms to measure the impact of partner countries' lockdowns on nominal export and import flows during 2020 and the first half of 2021, while also assessing the impact of the health crisis. The high time frequency and granularity of the data contribute to the identification of the impact of these obstacles on trade. We conclude that the detrimental impact of lockdowns is sizeable and broadly similar in exports and imports, and the impact of the health conditions is slightly stronger in exports. There is evidence that the detrimental impact of lockdowns was stronger for larger firms, for those with higher geographical concentration of trade, more integrated in global value chains and in the upper quartiles of the trade unit value distribution. The negative impact is also estimated to be larger for industries with high import content and for trade partners that are more important as sources of value added to be embodied in Portuguese exports. Results also suggest that exports adapted to the prevailing circumstances as of June 2020, but such an effect is not clear in imports.

o direito, perpétuo e sem limites geográficos, de arquivar e publicar esta dissertação através de exemplares impressos reproduzidos em papel ou de forma digital, ou por qualquer outro meio conhecido ou que venha a ser inventado, e de a divulgar através de repositórios científicos e de admitir a sua cópia e distribuição com objetivos educacionais ou de investigação, não comerciais, desde que seja dado crédito ao autor e editor.

In this study, we attempt to answer the question of whether stock market performance affects the government satisfaction rating in the long run in a sample period spanning 1984:Q1 to 2013:Q2 in the UK. We examine both the equilibrium relationship and the causality relationship between stock market performance and government satisfaction rating. The results indicate that the voters are sensitive to the economic shocks and hold responsible for the government. The empirical results confirm the responsibility hypothesis.

This paper proposes a stochastic frontier model with three composed errors, and therefore six error components. As in the metafrontier literature, firms belong to groups with a group-specific frontier. A firm has a level of short-run and long-run inefficiency relative to its group-specific frontier, as in existing models with two composed errors and four error components. But now there is also a group-specific inefficiency, that is, a shortfall of the group-specific frontier from the best practice metafrontier. The paper shows how to estimate this model and how to extract predictions of the various inefficiencies.

This work investigates the determinants of health care expenditures, such as drug prescriptions, inpatient care, and outpatient care, of the resident population of the Region of Friuli Venezia Giulia (Italy). The phenomenon of interest is examined here by considering a cross-sectional register-based dataset on individual expenditures exhibiting a cross-classified hierarchical structure. In fact, patients (about 1,000,000) are grouped by general practitioners and municipalities. Does the evidence in individual data analyses support the results of the micro and macroeconomic literature? The adoption of disaggregated data allows us to disentangle the role of the micro and macroeconomic determinants of the expenditures. Moreover, the degree of interdependence between neighbouring municipalities is measured by accounting for the spatial correlation in the error convolution. A feasible two-stage Heckit method has to be adapted to encompass the zero inflation issue, to consider the hierarchical structure of data and to study the spatial di↵usion process of the expenditures in the sample selection model framework. The main results on the determinants of health care expenditures at the macro-level are confirmed in our analysis on disaggregated data. On the contrary, however, the substitution e↵ect, which is typically observed in aggregated data, has not been confirmed by the present research. Moreover, the selection process appears to be relevant in drug prescriptions and outpatient care expenditures Luca Grassetti (orcid.org/0000-0003-1997-8001) and Laura Rizzi (orcid.

This paper adds to the recent body of research on fertility by estimating and testing censored poisson regression models and censored negative binomial regression models of household fertility decisions. A novel feature of this study is that in each case the censoring threshold varies from individual to individual. Also, a Lagrange multiplier or score test is used to investigate overdispersion. In these regression models the dependent variable is the number of children. In this situation, censored poisson regression models and censored negative binomial regression models have statistical advantages over OLS, uncensored poisson regression models, and uncensored negative binomial regression models. The censored models employed in this study are estimated using panel data collected from the Consumer Expenditure Survey compiled by the Bureau of Labor Statistics. The findings of this study support the fertility hypothesis of Becker and Lewis (1965-70).

As the Baby-Boomer generation approaches the retirement stage of the life cycle, understanding the implications of the labour market transition for individuals' wellbeing is increasingly important for policy making. In this article, we assess whether individuals successfully navigate the transition from work to retirement by analysing changes in subjective well-being with retirement using Australian panel data. To account for the fact that retirement is often a choice, we exploit social security eligibility rules to identify the causal effect of retirement on well-being. We find that life satisfaction significantly improves for the large majority of individuals who voluntarily retire from the labour force. However, there are also important disparities and individuals forced to retire early do not experience gains in life satisfaction with retirement. Moreover, the negative impact of involuntary retirement is greatest for individuals from disadvantaged backgrounds. We also present new evidence on intra-household retirement spillovers by assessing the effect of one partner's retirement circumstances on their spouse's life satisfaction. The article further extends the literature by examining the mechanisms through which retirement affects individuals' life satisfaction. We find that declines in life satisfaction are in part driven by an increase in financial hardship and reduced social interactions.

This paper develops a dynamic-network DEA (data envelopment analysis) model where total output is jointly produced from two sectors: a human capital sector and a physical capital sector. Each prefecture produces a final output and an intermediate product which is used to augment future physical capital. The optimization method allows future production possibilities to be enhanced if some final output in the current period is foregone so that larger amounts of the intermediate product can be produced. The goal is to choose the amounts of final output and intermediate product so as to maximize the size of the production possibility set. The method also allows identification of whether output is constrained by a lack of physical capital, a lack of human capital or a lack of both types of capital. We apply our method to 47 Japanese B Hirofumi Fukuyama

This paper develops a dynamic-network DEA (data envelopment analysis) model where total output is jointly produced from two sectors: a human capital sector and a physical capital sector. Each prefecture produces a final output and an intermediate product which is used to augment future physical capital. The optimization method allows future production possibilities to be enhanced if some final output in the current period is foregone so that larger amounts of the intermediate product can be produced. The goal is to choose the amounts of final output and intermediate product so as to maximize the size of the production possibility set. The method also allows identification of whether output is constrained by a lack of physical capital, a lack of human capital or a lack of both types of capital. We apply our method to 47 Japanese B Hirofumi Fukuyama

This paper considers testing for structural change of unknown form in the linear regression model as a problem of testing for goodness-of-fit. Transformations of recursive (or other LUS) residuals that reduce the problem to one of testing independently distributed uniform variables are presented. Exact empirical distribution function tests can then be applied without having to estimate unknown parameters. The tests are illustrated by their application to a money demand model. 1.

The a im o f this p a p e r is to a na lyze the re la tio nship s b e tw e e n c o m m o n sho c ks a ffe c ting the re a l e c o no m y a nd tho se und e rlying c o -fluc tua tio ns in U.S. fina nc ia l m a rke ts. In o rd e r to d o this, w e te st fo r links b e tw e e n the se c o m m o n fa c to rs a nd a lso use the e c o no m e tric the o ry o f no n-sta tio na ry p a ne l d a ta to e stim a te the re la tio nship s. The e stim a te s p ro ve the e xiste nc e o f sig nific a nt re la tio nship s b e tw e e n fina nc ia l a nd m a c ro e c o no m ic fa c to rs. It is a lso sho w n tha t the re a re fo rc e s p ulling U.S. fina nc ia l m a rke ts to m o ve .

In this work we revisit the retirement consumption puzzle using Italian panel data. As emphasised in the literature, the observed consumption drop might be due to unexpected wealth shocks at retirement which modify optimal consumption plans. Using an Euler equation approach, we test the impact of unexpected retirement on the consumption patterns of individuals around the age of retirement by using the panel component of the Survey of Household Income and Wealth (SHIW). This data set contains information on the expected age of retirement which can be used to distinguish between expected and unexpected retirement. Furthermore, we investigate the heterogeneous behaviour of individuals with different levels of education and wealth. We find evidence of a consumption drop at retirement especially for low-educated people and individuals with little wealth. The consumption drop at retirement, on average, does not seem to be a response to unexpected retirement. Disaggregating our sample, we find that the consumption drop persists among low-educated people with little wealth available, irrespective of whether retirement was expected or not. Highly educated people, conversely, do smooth their consumption, unless they have low wealth and are hit by an unexpected shock at retirement in which case they are forced to drop consumption.

This paper forms part of the ESRC funded project (Award No. L1382511013) "Business Cycle Volatility and Economic Growth: A Comparative Time Series Study", which itself is part of the Understanding the Evolving Macroeconomy Research programme.

In the literature using short-run timing restrictions to identify monetary policy shocks in vector-autoregressions (VAR) there is a debate on whether (i) contemporaneous real activity and prices or (ii) only data typically observed with high frequency should be assumed to be in the information set of the central bank when the interest rate decision is taken. This paper applies graphical modelling theory, a data-based tool, in a small-scale VAR of the US economy to shed light on this issue. Results corroborate the second type of assumption.

We examine the joint predictability of return and cash flow within a present value framework, by imposing the implications from a long-run risk model that allow for both time-varying volatility and volatility uncertainty. We provide new evidence that the expected return variation and the variance risk premium positively forecast both short-horizon returns and dividend growth rates. We also confirm that dividend yield positively forecasts long-horizon returns, but that it does not help in forecasting dividend growth rates. Our equilibrium-based ''structural'' factor GARCH model permits much more accurate inference than univariate regression procedures traditionally employed in the literature. The model also allows for the direct estimation of the underlying economic mechanisms, including a new volatility leverage effect, the persistence of the latent long-run growth component and the two latent volatility factors, as well as the contemporaneous impacts of the underlying ''structural'' shocks.

In this paper, we conduct choice experiments in Turkey and Ukraine on the valuation of a marine restoration programme in the Black Sea, to examine whether the value of environmental goods is sensitive to the source of public financing. We contribute to the debate on the optimal composition of public expenditure, an issue that can be controversial in times of financial crises. We discriminate between two funding regimes through the reallocation of public spending. The first proposes financing the marine restoration programme by reducing public expenditure for investments in renewable energy, and the second by reducing public expenditure for civil servants' training. The results reveal that the marginal value of public money depends on the funding source. Furthermore, attribute values are sensitive to the trade-off implied K. Remoundou (B) School of Management and Business

We investigate the association between age and medical spending in the U.S. using data from the Medical Expenditure Panel Survey (MEPS). We estimate a partial linear seminonparametric model and construct "pure" life-cycle profiles of health spending simultaneously controlling for time effects (i.e. institutional changes and business cycles effects) and cohort effects (i.e. generation specific conditions). We find that time and cohort effects introduce a significant estimation bias into predictions of health expenditures per age group, especially for individuals older than 60 years. The estimation biases introduced by cohort effects increase monotonically with age while time effects are non-monotone. Overall, cohort effect biases dominate time effect biases in magnitude for high age groups.

In this paper we aim at identifying stylized facts in order to suggest adequate models of spatial co-agglomeration of industries. We describe a class of spatial statistical methods to be used in the empirical analysis of spatial clusters. Compared to previous contributions using point pattern methods, the main innovation of the present paper is to consider clustering for bivariate (rather than univariate) distributions, which allows uncovering co-agglomeration and repulsion phenomena between the different industrial sectors. Furthermore we present the results of an empirical application of such methods to a set of European Patent Office (EPO) data and we produce a series of empirical evidences referred to the the pair-wise intra-sectoral spatial distribution of patents in Italy in the nineties. In this analysis we are able to identify some distinctive joint patterns of location between patents of different sectors and to propose some possible economic interpretations.

Ever since the end of the Great Recession, the US economy has experienced a period of mild inflation, which contradicts with the output-inflation relationship depicted by a traditional Phillips curve. This paper examines how the permanent output loss during the Great Recession has affected the ability of the Phillips curve to explain US inflation dynamics. We find great similarity among several established trend-cycle decomposition methods: potential output declined substantially after the Great Recession. Due to the fact that a lower level of potential output implies a lesser deflationary pressure, we then show that the Phillips curve does predict a period of mild inflation. This finding is largely consistent with the observed data.

In this evolutionary model, random shocks create differences in the rate of return on capital, while individual saving and investment behavior can reduce these differences over time. Firms with either low total factor productivity (TFP) or a low average return on capital are selected for exit, and new firms enter to take their place. As would be expected, a higher turnover rate improves TFP and reduces its variation. While we show that a higher turnover rate would result in a more positively skewed TFP distribution if exit selection is based directly upon TFP, we find that when we select firms for exit based on their average product of capital, the marginal impact of a higher turnover rate is to more negatively skew the TFP distribution. Overall, our simulations highlight the importance of considering the role selection may play in shaping the distribution of productivity when econometricians seek estimates of firm inefficiency.

This paper analyzes whether moderate weight reduction improves subjective health perception in obese individuals. Besides simple regression models, in a simultaneous equation framework we use randomized monetary weight loss incentives as instrument for weight change, to address possible endogeneity bias. In contrast to related earlier work that also employed instrumental variables estimation, identification does not rely on long-term, between-individuals weight variation, but on short-term, within-individual weight variation. Yet, our result does not suggest that the simple regressions suffer from much endogeneity bias, since instrumental variables estimation yields similar—though far noisily estimated and statistically insignificant—estimates. In qualitative terms, our results do not contradict previous findings pointing to weight loss in obese individuals resulting in improved subjective health. Our results suggest that a reduction of body weight by one BMI unit is associated with...

This paper investigates the factors that determine differences across OECD countries in health outcomes, using data on life expectancy at age 65, over the period 1960 to 2007. We estimate a production function where life expectancy depends on health and social spending, lifestyle variables, and medical innovation. Our first set of regressions includes a set of observed medical technologies by country. Our second set of regressions proxy technology using a spatial process. The paper also tests whether in the long-run countries tend to achieve similar levels of health outcomes. Our results show that health spending has a significant and mild effect on health out-comes, even after controlling for medical innovation. However, its short-run adjustments do not seem to have an impact on health care productivity. Spatial spill overs in life expectancy are significant and point to the existence of interdependence across countries in technology adoption. Furthermore, nations with initial low levels of life expectancy tend to catch up with those with longer-lived populations.

This paper considers various estimators using panel data seemingly unrelated regressions (SUR) with spatial error correlation. The true data generating process is assumed to be SUR with spatial error of the autoregressive or moving average type. Moreover, the remainder term of the spatial process is assumed to follow an error component structure. Both maximum likelihood and generalized moments (GM) methods of estimation are used. Using Monte Carlo experiments, we check the performance of these estimators and their forecasts under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous versus homogeneous panel data models.

We propose conduct parameter based market power measures within a model of price discrimination, extending work by and to certain forms of second degree price discrimination. We use our model to estimate the market power of U.S. airlines in a price discrimination environment. We …nd that a slightly modi…ed version of our original theoretical measure is positively related with market concentration. Moreover, on average, market power for high-end segment is greater than that of low-end segment.

A factor structure for VAR model error terms is adopted to examine the dynamic relationships of major macroeconomic time series. The structure, which is testable, is used to trace the consequences of a contemporaneously "ceteris paribus" (or idiosyncratic) change in each variable in the VAR model. The impulse responses to idiosyncratic shocks are shown to be a dynamic representation of the Granger causality. In the analyses of the US monthly data from 1954 to 2011 for four key variables, inflation is found to respond negatively (positively) to an increase in unemployment (the federal funds rate), holding other variables contemporaneously fixed. The real variables (output and unemployment) appear unresponsive to idiosyncratic changes in the nominal variables (the federal funds rate and inflation). A common factor is observed to have a positive effect on unemployment and negative effects on output, inflation and the federal funds rate.

A factor structure for VAR model error terms is adopted to examine the dynamic relationships of major macroeconomic time series. The structure, which is testable, is used to trace the consequences of a contemporaneously "ceteris paribus" (or idiosyncratic) change in each variable in the VAR model. The impulse responses to idiosyncratic shocks are shown to be a dynamic representation of the Granger causality. In the analyses of the US monthly data from 1954 to 2011 for four key variables, inflation is found to respond negatively (positively) to an increase in unemployment (the federal funds rate), holding other variables contemporaneously fixed. The real variables (output and unemployment) appear unresponsive to idiosyncratic changes in the nominal variables (the federal funds rate and inflation). A common factor is observed to have a positive effect on unemployment and negative effects on output, inflation and the federal funds rate.

Di erent stochastic simulation methods are used in order to check the robustness of the outcome of policy simulations with a macroeconometric model. A macroeconometric disequilibrium model of the West German economy is used to analyze a reform proposal for the tax system. The model was estimated with quarterly data for the period1960 to 1994, the presently possible margin. Because of nonlinearities con dence intervals for the simulation results have t o be obtained by means of stochastic simulations. The main contribution of this paper consists in presenting the simulation results. The robustness of these results is analyzed using di erent approaches to stochastic simulation. In particular, di erent methods for the generation of uniform error terms and their conversion to normal variates are applied. These methods include standard approaches as well as quasi{Monte Carlo methods. We are indebted to H. Buscher for his comments on a rst draft of the paper, I. Czekalla for valuable research assistance and to F. Higginson for her support in the translation of parts of a preliminary version of this paper.

This paper proposes new fuzzy measures of monetary poverty and also non-monetary deprivation, providing an economic interpretation of the parameters involved. For non-monetary deprivation, the paper provides a step-by-step procedure: dimensions or groupings of initial items of deprivation are identified using explanatory and confirmatory factor analyses, and a weighting system is applied for the aggregation of individual items into the dimension they represent. The methodology is applied to European Union countries using European Union-Statistics on Income and Living Conditions (EU-SILC) data for the 2011 survey wave.

This paper evaluates the appropriateness of a Linear Market Model (LMM) which allows for systematic covariance (beta) risk. The performance of LMM will be compared against two extensions, a comparison having yet to be undertaken in the literature. The first extension is the Time-varying Linear Market Model (Tv-LMM) which allows for time-varying systematic covariance risk in the form of a mean reverting state space model via the Kalman filter. The second extension is the multivariate Time-varying Linear Market Model (MTv-LMM) which allows for the time-varying systematic covariance risk of country stock market correlation structure via the multivariate KFMR. The comparison between LMM, Tv-LMM and MTv-LMM, is implemented utilising weekly data collected from several developed and emerging markets for the periods; before and after financial crisis in October 2008, and forecasting 2 years forwards. The empirical findings of that process overwhelmingly support the use of the Multivariate Time-varying Linear Market Model (MTv-LMM) when modelling and forecasting stock market returns, especially for developed stock markets. CAPM • Multivariate model • State space model • Stock market returns • Systematic covariance (beta) risk • Time-varying beta JEL Classification C53 • G12 • G17 B Serdar Neslihanoglu

This paper evaluates the appropriateness of a Linear Market Model (LMM) which allows for systematic covariance (beta) risk. The performance of LMM will be compared against two extensions, a comparison having yet to be undertaken in the literature. The first extension is the Time-varying Linear Market Model (Tv-LMM) which allows for time-varying systematic covariance risk in the form of a mean reverting state space model via the Kalman filter. The second extension is the multivariate Time-varying Linear Market Model (MTv-LMM) which allows for the time-varying systematic covariance risk of country stock market correlation structure via the multivariate KFMR. The comparison between LMM, Tv-LMM and MTv-LMM, is implemented utilising weekly data collected from several developed and emerging markets for the periods; before and after financial crisis in October 2008, and forecasting 2 years forwards. The empirical findings of that process overwhelmingly support the use of the Multivariate Time-varying Linear Market Model (MTv-LMM) when modelling and forecasting stock market returns, especially for developed stock markets. CAPM • Multivariate model • State space model • Stock market returns • Systematic covariance (beta) risk • Time-varying beta JEL Classification C53 • G12 • G17 B Serdar Neslihanoglu

This paper focuses on the problem of analyzing how factors impact hunger across states when hunger is ill-de®ned. Hunger (which is a latent variable) is presumed to depend on macroeconomic, legislation, policy, and demographic variables. Based on the Bayesian method of a posterior odds ratios, we ®nd that the high school graduation rate appears to be the single most important factor we identify which a¨ects the perceived hunger measure.

This article develops a simple, but informative, approach to measure technical changes by applying the Malmquist index framework using data envelopment analysis (DEA). A set of directional vectors is used to capture complete information regarding the overall shift in the technology frontier; we then visualize the DEA frontiers in the output space. This approach deals with the problems of sample dependence and non-circularity of technical change measures. It allows us to measure output-byoutput technical change. Furthermore, the geometric mean of the technical change measures derived using this approach satisfies circularity. The application of Malmquist indices to the panel datasets of agricultural production in the Brazilian Amazon during the period 1975-1995 indicates a non-Hicks-neutral technical change, with intersection of frontiers during both the 1975-1985 and the 1985-1995 sub-periods. We find moderate progress in cattle production and annual crops, and a decline in perennial crops (bananas). Technological progress is a modest 0.7 % during the period 1975-1995 on average. In addition, comparisons with the sample-dependent measures in the preceding studies demonstrate that these indices are usually sensitive to the distribution of actual sampled data points.

This paper presents Genetic Matching, a method of multivariate matching, that uses an evolutionary search algorithm to determine the weight each covariate is given. Both propensity score matching and matching based on Mahalanobis distance are limiting cases of this method. The algorithm makes transparent certain issues that all matching methods must confront. We present simulation studies that show that the algorithm improves covariate balance, and that it may reduce bias if the selection on observables assumption holds. We then present a reanalysis of a number of datasets in the LaLonde (1986) controversy.

How much knowledge is there in an economy? In recent years, data on the mix of products that countries export has been used to construct measures of economic complexity that estimate the knowledge available in an economy and predict future economic growth. Here we introduce a new and simpler metric of economic complexity (ECI+) that measures the total exports of an economy corrected by how difficult it is to export each product. We use data from 1973 to 2013 to compare the ability of ECI+, the Economic Complexity Index (ECI), and Fitness complexity, to predict future economic growth using 5, 10, and 20-year panels in a pooled OLS, a random effects model, and a fixed effects model. We find that ECI+ outperforms ECI and Fitness in its ability to predict economic growth and in the consistency of its estimators across most econometric specifications. On average, one standard deviation increase in ECI+ is associated with an increase in annualized growth of about 4% to 5%. We then combine ECI+ with measures of physical capital, human capital, and institutions, to find a robust model of economic growth. The ability of ECI+ to predict growth, and the value of its coefficient, is robust to these controls. Also, we find that human capital, political stability, and control of corruption; are positively associated with future economic growth, and that initial income is negatively associated with growth, in agreement with the traditional growth literature. Finally, we use ECI+ to generate economic growth predictions for the next 20 years and compare these predictions with the ones obtained using ECI and Fitness. These findings improve the methods available to estimate the knowledge intensity of economies and predict future economic growth.

We develop a model of the firm's maximization programme i n which the firm's capital structure is a non linear function of a vector of costs including asymmetric information costs and is subject to a debt ceiling. Using conditional quantile regression methods, we test for the existence of such a non-linearity in a heterogeneous sample of UK firms and demonstrate that, by exploiting more fully the distribution of leverage, this technique yields new insights into the choice of leverage ratio. Not only is the estimated effect of the explanatory variables different at different quantiles of the distribution, we find evidence that the effect of a variable changes sign between low leveraged and high leveraged firms.

This paper investigates whether the real interest rate parity (RIRP) is valid during the three waves of globalizations that occurred in the last 150 years (1870-1914, 1944-1971, 1989 to the present). If any, these periods should favor RIRP, since globalization is a process where economies and financial markets become increasingly integrated into a global economic system. In contrast to the existing literature, we model the departures from RIRP as a long-term memory process and apply fractional integration methods on a sample of real interest rate differentials of seven developed countries: France, Germany, Holland, Italy, Japan, Spain, and the UK across the three globalization waves paired against the USA. We compute impulse response functions (IRF) to gain further insight into the memory characteristics of the RIRP differential processes and provide half-life estimates. We find that deviations from RIRP are mean reverting, providing robust evidence of real interest rate convergence during the three globalization waves. We shed further light on financial and commodity market integration during the three globalization waves by assessing the memory properties of uncovered interest rate parity (UIP) and relative purchasing power parity (PPP) differential processes. We find that deviations from relative PPP and UIP are not always mean-reverting processes. RIRP, relative PPP, and UIP hold simultaneously only in 7 out of 21 cases; RIRP and UIP hold in 11 out of 21 cases; RIRP hold without the support of relative PPP and UIP in 3 out of 21 cases. Thus, the evidence in favor of real interest rate convergence appears to be driven more by UIP than relative PPP. All these results are, to the authors knowledge, new to the literature.

This study explores the influence of financial leverage and of management competence on firm performance using a sample of 102 listed firms in the Athens Stock Exchange. It is found that leverage contributes significantly to sales growth, stock returns, and profitability due to management competence.

'Modern' theories of the Phillips curve inadvertently imply that inflation is an integrated or near integrated process but this implication is strongly rejected using United States data. Alternatively, if we assume that inflation is a stationary process around a shifting mean (due to changes in monetary policy) then any estimate of long-run relationships in the data will suffer from a 'small-sample' problem as there are too few stationary inflation 'regimes'. Using the extensive literature on identification of structural breaks we identify inflation regimes which are used in turn to estimate with panel data techniques the United States long-run Phillips curve.

We examine the relationship between inflation targeting and the behavior of the level and volatility of inflation for eight Asian countries over the period 1987-2013. In contrast to existing studies that rely upon time series methods, we employ a novel panel GARCH model that accounts for heterogeneity and interdependence across countries. Our main contribution is to shed new light on the inflation targeting credibility hypothesis based on lower inflation and inflation volatility as well as on the correlation between unanticipated inflation shocks within a panel GARCH framework. We find strong evidence of a reduction in the level of inflation that operates from the impact of actual inflation targets in the Philippines, South Korea and Thailand. We also find that the adoption of inflation targeting helped lower inflation volatility in the Philippines and South Korea. Overall, the results suggest that Asian inflation targeting regimes are more credible in terms of reducing the level of inflation than lowering inflation volatility. There is also evidence that the covariance of inflation shocks among inflation targeting and non-targeting countries tends to increase.