Modelling Spatial Regimes in Farms Technologies

We exploit the information derived from geographical coordinates to endogenously identify spatial regimes in technologies that are the result of a variety of complex, dynamic interactions among site-specific environmental variables and farmer decision making about technology, which are often not observed at the farm level. Controlling for unobserved heterogeneity is a fundamental challenge in empirical research, as failing to do so can produce model misspecification and preclude causal inference. In this article, we adopt a two-step procedure to deal with unobserved spatial heterogeneity, while accounting for spatial dependence in a cross-sectional setting. The first step of the procedure takes explicitly unobserved spatial heterogeneity into account to endogenously identify subsets of farms that follow a similar local production econometric model, i.e. spatial production regimes. The second step consists in the specification of a spatial autoregressive model with autoregressive disturbances and spatial regimes. The method is applied to two regional samples of olive growing farms in Italy. The main finding is that the identification of spatial regimes can help drawing a more detailed picture of the production environment and provide more accurate information to guide extension services and policy makers

Econometrics meets sentiment : an overview of methodology and applications

The advent of massive amounts of textual, audio, and visual data has spurred the development of econometric methodology to transform qualitative sentiment data into quantitative sentiment variables, and to use those variables in an econometric analysis of the relationships between sentiment and other variables. We survey this emerging research field and refer to it as sentometrics, which is a portmanteau of sentiment and econometrics. We provide a synthesis of the relevant methodological approaches, illustrate with empirical results, and discuss useful software

FDI and Taxation: A Meta-Study

Despite the continuing political interest in the usefulness of tax competition and tax coordination as well as the wealth of theoretical analyses, it still remains open whether or when tax competition is harmful. Moreover, the influence of tax differentials on multinationals' decisions is still insufficiently analyzed. Thus, economists have increasingly resorted to empirical analysis in order to gain insights on the elasticity of FDI with respect to company taxation. As a result, the empirical literature on taxation and international capital flows has grown to a similar abundance during the last 25 years as the respective theoretical literature. Its heterogeneity leads to a rising need for concise reviews on the existing empirical evidence. In this paper we extend former meta-analyses on FDI and taxation in three ways. First, we add the most recent publications unconsidered in meta-analyses up-to-date. Second, we apply a different methodology by using a broad set of meta-regression estimators and explicitly discuss which one is most suitable for application to our meta-data. Third, we address some important issues in research on FDI and taxation to the clarification of which meta-analysis can make valuable contributions. These issues are mainly: The influence of variables which might moderate effects of tax differentials (e.g. public spending), the implications of using aggregate FDI data as opposed to firm-level information on measured tax effects, the implications of bilateral effective tax rates, and the possible presence of publication bias in primary research. --Corporate Income Taxation,Foreign Direct Investment,Meta Analysis

FDI and Taxation: A Meta-Study

Despite the continuing political interest in the usefulness of tax competition and tax coordination as well as the wealth of theoretical analyses, it still remains open whether or when tax competition is harmful. Moreover, the influence of tax differentials on multinationals’ decisions is still insufficiently analyzed. Thus, economists have increasingly resorted to empirical analysis in order to gain insights on the elasticity of FDI with respect to company taxation. As a result, the empirical literature on taxation and international capital flows has grown to a similar abundance during the last 25 years as the respective theoretical literature. Its heterogeneity leads to a rising need for concise reviews on the existing empirical evidence. In this paper we extend former meta-analyses on FDI and taxation in three ways. First, we add the most recent publications unconsidered in meta-analyses up-to-date. Second, we apply a different methodology by using a broad set of meta-regression estimators and explicitly discuss which one is most suitable for application to our meta-data. Third, we address some important issues in research on FDI and taxation to the clarification of which meta-analysis can make valuable contributions. These issues are mainly: The influence of variables which might moderate effects of tax differentials (e.g. public spending), the implications of using aggregate FDI data as opposed to firm-level information on measured tax effects, the implications of bilateral effective tax rates, and the possible presence of publication bias in primary research.corporate income taxation, foreign direct investment, meta analysis

Measurement in marketing

We distinguish three senses of the concept of measurement (measurement as the selection of observable indicators of theoretical concepts, measurement as the collection of data from respondents, and measurement as the formulation of measurement models linking observable indicators to latent factors representing the theoretical concepts), and we review important issues related to measurement in each of these senses. With regard to measurement in the first sense, we distinguish the steps of construct definition and item generation, and we review scale development efforts reported in three major marketing journals since 2000 to illustrate these steps and derive practical guidelines. With regard to measurement in the second sense, we look at the survey process from the respondent's perspective and discuss the goals that may guide participants' behavior during a survey, the cognitive resources that respondents devote to answering survey questions, and the problems that may occur at the various steps of the survey process. Finally, with regard to measurement in the third sense, we cover both reflective and formative measurement models, and we explain how researchers can assess the quality of measurement in both types of measurement models and how they can ascertain the comparability of measurements across different populations of respondents or conditions of measurement. We also provide a detailed empirical example of measurement analysis for reflective measurement models

Heuristic model selection for leading indicators in Russia and Germany

Business tendency survey indicators are widely recognized as a key instrument for business cycle forecasting. Their leading indicator property is assessed with regard to forecasting industrial production in Russia and Germany. For this purpose, vector autoregressive (VAR) models are specified and estimated to construct forecasts. As the potential number of lags included is large, we compare full–specified VAR models with subset models obtained using a Genetic Algorithm enabling ’holes’ in multivariate lag structures. The problem is complicated by the fact that a structural break and seasonal variation of indicators have to be taken into account. The models allow for a comparison of the dynamic adjustment and the forecasting performance of the leading indicators for bothLeading indicators, business cycle forecasts, VAR, model selection, genetic algorithms.

Heuristic model selection for leading indicators in Russia and Germany

Business tendency survey indicators are widely recognized as a key instrument for business cycle forecasting. Their leading indicator property is assessed with regard to forecasting industrial production in Russia and Germany. For this purpose, vector autoregressive (VAR) models are specified and estimated to construct forecasts. As the potential number of lags included is large, we compare full–specified VAR models with subset models obtained using a Genetic Algorithm enabling ’holes’ in multivariate lag structures. The problem is complicated by the fact that a structural break and seasonal variation of indicators have to be taken into account. The models allow for a comparison of the dynamic adjustment and the forecasting performance of the leading indicators for both countries revealing marked differences between Russia and Germany.Leading indicators, business cycle forecasts, VAR, model selection, genetic algorithms

Econometrics: A bird's eye view

As a unified discipline, econometrics is still relatively young and has been transforming and expanding very rapidly over the past few decades. Major advances have taken place in the analysis of cross sectional data by means of semi-parametric and non-parametric techniques. Heterogeneity of economic relations across individuals, firms and industries is increasingly acknowledge and attempts have been made to take them into account either by integrating out their effects or by modeling the sources of heterogeneity when suitable panel data exists. The counterfactual considerations that underlie policy analysis and treatment evaluation have been given a more satisfactory foundation. New time series econometric techniques have been developed and employed extensively in the areas of macroeconometrics and finance. Non-linear econometric techniques are used increasingly in the analysis of cross section and time series observations. Applications of Bayesian techniques to econometric problems have been given new impetus largely thanks to advances in computer power and computational techniques. The use of Bayesian techniques have in turn provided the investigators with a unifying framework where the tasks and forecasting, decision making, model evaluation and learning can be considered as parts of the same interactive and iterative process; thus paving the way for establishing the foundation of the "real time econometrics". This paper attempts to provide an overview of some of these developments

FDI and taxation : a meta-study

Despite the continuing political interest in the usefulness of tax competition and tax coordination as well as the wealth of theoretical analyses, it still remains open whether or when tax competition is harmful. Moreover, the influence of tax differentials on multinationals' decisions is still insufficiently analyzed. Thus, economists have increasingly resorted to empirical analysis in order to gain insights on the elasticity of FDI with respect to company taxation. As a result, the empirical literature on taxation and international capital flows has grown to a similar abundance during the last 25 years as the respective theoretical literature. Its heterogeneity leads to a rising need for concise reviews on the existing empirical evidence. In this paper we extend former meta-analyses on FDI and taxation in three ways. First, we add the most recent publications unconsidered in meta-analyses up-to-date. Second, we apply a different methodology by using a broad set of meta-regression estimators and explicitly discuss which one is most suitable for application to our meta-data. Third, we address some important issues in research on FDI and taxation to the clarification of which meta-analysis can make valuable contributions. These issues are mainly: The influence of variables which might moderate effects of tax differentials (e.g. public spending), the implications of using aggregate FDI data as opposed to firm-level information on measured tax effects, the implications of bilateral effective tax rates, and the possible presence of publication bias in primary research