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We present a semiparametric method to estimate group-level dispersion, which is particularly effective in the presence of censored data. We apply this procedure to obtain measures of occupation-specific wage dispersion using top-coded administrative wage data from the German IAB Employment Sample. We then relate these robust measures of earnings risk to the risk attitudes of individuals working in these occupations. We find that willingness to take risk is positively correlated with the wage dispersion of an individual’s occupation.

The aim of this paper is the study of Tuscan municipalities public ex- penditure efficiency, with particular attention on the effect of the municipal size, through a DEA analysis. In line with the existing literature, the study includes a second stage analysis to explain municipal ineciencies through a Tobit regression. The results obtained through the DEA analysis and explained by the Tobit regression appear consistent and could represent a sound suggestion to correct the expenditure of the inefficient municipalities. The new evidences related to the efficiency analysis of local government described in the paper provide an important contribution to the current debate, being this the first study carried out on Tuscan municipalities and introducing a new indicator for the computation of the eciency scores which offer a new way of procedure. Moreover, the study addresses the long debated issue on municipal size proving that the municipal size really affects the effciency of the public expenditure (i.e. the bigger is a munici- pality, the greater is its level of public spending efficiency).

This paper studies the semiparametric binary response model with interval data investigated by Manski and Tamer (2002, MT). In this partially identified model, we propose a new estimator based on MT's modified maximum score (MMS) method by introducing density weights to the objective function, which allows us to develop asymptotic properties of the proposed set estimator for inference. We show that the density-weighted MMS estimator converges to the identified set at a nearly cube-root-n rate. Further, we propose an asymptotically valid inference procedure for the identified region based on subsampling. Monte Carlo experiments provide supports to our inference procedure.

The Tobit model (censored regression model) is an important basic model appearing in many applications in economics. In this paper we consider a duration Tobit model in which a duration variable which counts the number of times the data is being censored is included as a covariate. We show that in this case, the dependent variable eventually becomes degenerate, which makes the asymptotic Fisher information matrix singular, rendering the standard methods of asymptotic inference inapplicable. We provide a simulation study and an empirical application to support our results.

We estimated the progressive, structural synchronization of the Mexican growth cycle with that of the US (total and industrial) for 1980.1-2013.4. By applying the Quandt-Andrews (1993) and Bai-Perron (2003) unknown-breakpoint tests, we identified that before 1994.4 there was no statistically significant relationship between the Mexican GDP growth cycle and the US industrial output cycle, but a weak (statistically significant) relationship with total US GDP cycle. However, since 1997.4 and particularly since 2001.2, there is a vast and increasing synchronization and determination from the US industrial cycle to the Mexican cycle (R2 = 0.96). The degrees of freedom of Mexican domestic economic policy have thus drastically decreased.

The purpose of this study is to analyze factors affecting Foreign Direct Investment (FDI) in countries with a high rate of FDI from 2005 to 2011, by examining the effects of the 2008 crisis. A Panel Tobit model is estimated in order to see the effects on the whole period, and classical Tobit models for each year are estimated separately for the purpose of examining the effects prior to, after and during the crisis, in detail. In the Tobit models, estimated separately for each year, the labor rate and inflation rate variables that are significant in panel Tobit models are not found significant for any of the examined years. As the balance of current accounts is found to be significant both prior to and after the crisis, it can be said that the effect of this variable on FDI is not affected by the crisis. Although there are studies examining factors affecting the FDI in the crisis period, to the best of our knowledge this is the only study using panel Tobit and classical Tobit models to that end. © 2015, Econjournals. All rights reserved.

The paper investigates the households’ preference for electricity service reliability. Using a contingent valuation survey; we elicit Beninese urban households’ willingness to pay (WTP) to avoid power outages. In the study respondents are asked to state their WTP for avoiding six different unplanned outages. We therefore apply a random parameter Tobit model on a temporal panel data since there is cross-sectional heterogeneity and a proportion of zero responses. Based on the estimations, we find that the preference for electricity service reliability among household is higher during night time and weekend days and depends positively on the duration of the outages. These results tend to validate the thesis that households preference for electricity service reliability strongly depends on leisure time

This paper estimates relative risk aversion using the observed shares of risky assets and characteristics of households from the Household Finance and Consumption Survey of the European Central Bank. Given that the risky share is a fractional response variable belonging to [0, 1], this paper proposes a censored fractional response estimation method using extremal quantiles to approximate the censoring thresholds. Considering that participation in risky asset markets is costly, I estimate both the heterogeneous relative risk aversion and participation cost using a working sample that includes both risky asset holders and non-risky asset holders by treating the zero risky share as the result of heterogeneous self-censoring. Estimation results show lower participation costs and higher relative risk aversion than what was previously estimated. The estimated median relative risk aversions of eight European countries range from 4.6 to 13.6. However, the results are sensitive to households’ perception of the risky asset market return and volatility.

Although it is often asserted that the housing cost burden is one of the key determinants of household economic hardship, in practice the linkage between the two has been rarely explored. The focus has been instead on the role played by income or other socio-economic determinants of household hardship. However, housing costs represent one of the most significant outlays in a household balance. The burden represented by housing costs may indeed cause households to reduce non-housing expenditure such as health care, education, food and clothing, thus creating serious household economic hardship. The primary goal of this study is to contribute on the literature on poverty by looking at households economic hardship in relation to the housing cost burden. In particular, our focus is to relate economic hardship with home-ownership status, by jointly estimating the burden of housing costs for renters versus home-owners paying mortgage. Using microdata from the European Union Statistics on Income and Living Conditions dataset (EU-SILC) regarding five European countries (Italy, Germany, UK, Spain and France) we are able to exploit two indicators of housing cost burden and several indicators of household economic and financial hardship to examine the predictive power of housing costs in explaining family economic hardship. Furthermore, we jointly estimate the effect of the housing cost burden for renters versus home-owners paying mortgage. Results show that housing costs represent a non negligible burden in all the five European countries. Moreover, home ownership is found to significantly reduce household hardship status.

We examine possible accuracy gains from forecast averaging in the context of interval forecasts of electricity spot prices. First, we test whether constructing empirical prediction intervals (PI) from combined electricity spot price forecasts leads to better forecasts than those obtained from individual methods. Next, we propose a new method for constructing PI--Quantile Regression Averaging (QRA)--which utilizes the concept of quantile regression and a pool of point forecasts of individual (i.e. not combined) models. While the empirical PI from combined forecasts do not provide significant gains, the QRA-based PI are found to be more accurate than those of the best individual model--the smoothed nonparametric autoregressive model.

In this paper, we present a model that can be viewed as an extension of the traditional Tobit model. As opposed to that specific model, ours also accounts for the the fixed costs of car ownership. That extension is needed since being carless is an option for many households in societies that have a good system of public transportation, the main reason being that carless households wish to save the fixed costs of car ownership. So far, no existing model can adequately map the impact of these fixed costs on car ownership. The Multiple Discrete-Continuous Extreme Value Model (MDCEV) with fixed costs fills this gap. In fact, this model can evaluate the effect of policies intended to influence household behaviour with respect to car ownership, which can be of great interest to policy makers. Our model makes it possible to compute the effect of policies such as taxes on fuel or on car ownership on both the share of carless households and the average driving distance. We calibrated the model using data on Swiss private households in order to forecast were then able to forecast responses to policies. One result of particular interest that cannot be produced by other models is the evaluation of the impact of a tax on car ownership. Our results show that a tax on car ownership has a much lower impact on aggregate driving demand – per unit of tax revenues – than a tax on fuel.

Using the Markov-regime switching technique, this paper attempts to explain what drives the US gross fixed capital investment at an aggregate level. The focus of the paper is on the role of the cost of capital in determining the probability of switching between high and low investment-growth regimes. Whilst the bulk of the investment literature is concentrated on companylevel Tobin’s q to explain company-level investment, we calculate an aggregate Tobin’s q for the US non-farm, non-financial corporate sector, to analyse how the cost of capital impacts the non-linear relationship between investment and «q».

We study the efficiency of state stimulating methods to attract investments into the timber industry development by logit, probit and tobit panel data models. Оur estimates reveal the most efficient stimulating methods of attracting investments into the wood sector. The approach can be widespread to other sectors of the economy.

"Using a representative establishment data set for Germany, I show that, in line with the existing literature for several countries, firms' adjustment costs for employment are characterized by a fixed and convex functional form. Furthermore, they are asymmetric with dismissal costs exceeding hiring costs. An analysis of firms' adjustment in the period 1996 - 2010 also indicates that adjustment behavior has changed over time. Comparing the employment adjustment in the two observed business cycles comprising the years 1996 - 2003 and 2004 - 2010, I find that the adjustment speed was higher in the second business cycle indicating that adjustment costs have fallen in recent years." (Author's abstract, IAB-Doku) ((en))

The article aims to look at the long-run equilibrium relationship between per capita greenhouse gas emissions and per capita real GDP (EKC hypothesis) in an asymmetric framework using the non-linear threshold cointegration and error correction methodology for Polish economy during the period 2000 to 2012 (quarterly data). To test the robustness of the results the additional explanatory variable (per capita energy consumption) is added to the EKC model. The EKC hypothesis is tested using threshold autoregressive (TAR) and momentum threshold autoregressive (MTAR) cointegration method. Moreover, the threshold error correction model (TECM) is implemented in order to examine both the short-run and the long-run Granger-causal relationship between per capita greenhouse gas emissions and per capita income. We found strong evidence in favour of the EKC hypothesis for the Polish case and additionally we confirmed that adjustment of deviations toward the long-run equilibrium is asymmetric.

Based on a three-equation model for initial firm size, survival, and firm growth we estimate firm-specific transition probabilities between size classes of the firm size distribution. This allows to analyze counterfactual scenarios that assess the impact of changes in exogenous variables on the intra-distribution dynamics of the firm size distribution. We find that a counterfactual decrease in average firm age increases the exit hazard of young firms, and at the same time reduces the probability of observing high-growth firms. An increase in the industry-wide entry rate and an increase in market growth, by contrast, have virtually no impact on the intra-distribution dynamics of the firm size distribution. Finally, a larger birth size increases the probability for the youngest and smallest firms to become high-growth firms. Copyright 2014 The Author 2013. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved., Oxford University Press.

Informal payments for health care are common in most former communist countries. This article explores the demand side of these payments in Albania. Using tobit and Heckman selection models we control for individual determinants of informal payments in outpatient and inpatient health care. Propensity score matching (PSM) techniques are used to investigate the changes in the characteristics of people paying informally over the different years. Our findings suggest that vulnerable groups in society remain less protected against such payments and policy measures have not reached the most deprived regions of the country.

Sample selection bias as a specification error This paper discusses the bias that results from using non-randomly selected samples to estimate behavioral relationships as an ordinary specification error or «omitted variables» bias. A simple consistent two stage estimator is considered that enables analysts to utilize simple regression methods to estimate behavioral functions by least squares methods. The asymptotic distribution of the estimator is derived.

This article attempts to compare conclusions made about market contagion based on the periods indicated by using the Markov-switching model and based on a range for unconditional correlations as well as on arbitrary arrangements. DCC-model was used to control for correlation change over time. Determination of extremely high correlations by using a range for unconditional correlations and the MS(3) switching model yields similar results regarding conclusions about the occurrence of the process of contagion in a market. Conclusions about contagion are, however, made at a higher significance level in the case of the switching model.

The purpose of this study is to examine the impact of inflation on agricultural prices. The empirical model developed in that respect was estimated for a panel of twenty eight developed and eighty three developing countries over the period 1980-2007 using panel smooth transition regression technique. The findings indicate that the impact of inflation on the agricultural prices is positive in low inflation regime and is negative in high inflation regime. Therefore, we conclude that the impact of the inflation on the agriculture prices is positive in the developed countries in which low inflation rates are observed and is negative in the developing countries in which high inflation rates are observed.

In the country-wide providing the efficiency will only be provided by distributing the resources in the non-efficient provinces and regions well-balanced by correcting the deficiencies and by building separate plans. For this purpose, the efficiency of Turkey’s agriculture sector in 2009 on the basis of provinces and regions by using two-stage data envelopment analysis (DEA) method is analyzed, the factors that have an impact on productivity are determined and the differences between provinces and regions are focused on. Firstly, an input-oriented DEA was performed by using 4 inputs and 1 output under variable returns to scale assumption. While the average technical efficiency was found to be 75%, it was understood that the cost of agricultural labour force and energy needed to be reduced. Secondly, the Tobit regression model was used to analyse the relation between the technical efficiency values of the provinces and the variables considered to have an external impact on the agricultural productivity. As a result of the predicted model; precipitation per m2, the households engaged in agriculture, literacy ratio and ratio of asphalt roads were determined as variables which contribute the agricultural efficiency of the provinces. Furthermore, regional efficiency differences were observed and results were evaluated.

Using 11 years of monthly Italian bank-by-bank data, this paper correlates the bilateral amounts and the identity of each interbank borrower and lender with a long list of explanatory variables. The results show that interbank customer relationships, i.e. stable and strong relationships between pairs of borrowing and lending banks, do exist in Italy, that they persist over time, and that they functioned well during the crisis, enabling the healthier banks to provide and the troubled ones to receive funds.

This paper describes a methodology to calculate a spatial cost of living index using Colombian data for 2006 that takes into consideration the microeconomic behavior of households. Using the Almost Ideal Demand System and recovering the expenditure functions for the 23 main Colombian cities, the index proposed is compared to the traditional methodologies used to calculate the regional basket of goods in the country and to an alternative methodology proposed by Romero (2005). This comparison suggests that when the substitution effects are not considered, and the same basket of goods is evaluated in every city, the index is biased, and this bias increases when the difference between cities increases. For reducing the bias, we use a microeconomic approach that keeps the households' level of utility constant and allows substitution among different baskets of goods. According to our calculations, Bogota is still the most expensive city in the country followed by Armenia, Cali, Bucaramanga and Ibague.

The French wholesale market is set to expand in the next few years under European pressure and national decisions. In this paper, we assess the forecasting ability of several classes of time series models for electricity wholesale spot prices at a day-ahead horizon in France. Electricity spot prices display a strong seasonal pattern, particularly in France given the high share of electric heating in housing during winter time. To deal with this pattern, we implement a double temporal segmentation of the data. For each trading period and season, we use a large number of specifications based on market fundamentals: linear regressions, markov-switching models, threshold models with a smooth transition. Non-linear models designed to capture the sudden and fast-reverting spikes in the price dynamics yield more accurate forecasts. Modeling each season independently also leads to better results. Finally, pooling forecasts gives more reliable results. Individual models are generally superior but their performance is more unstable across hours and seasons.

We assess students' ability to forecast future earnings by using data on expected wages self-reported by college students with different graduation horizons. We find a significant gender gap, by which wage expectations are systematically lower for women than for men. However, women do not fully account for the gender gap in their future earnings. We also find that student performance, degree type, and graduation horizon play a relevant role in wage forecasts. In any case, students' expectations do not conform market wages but become more realistic as they approach graduation. We are in debt with Juanjo Dolado and Ricardo Mora for valuable comments. We acknowledge research funding from the Spanish Ministry of Finance and Competitiveness, Grant Nos. ECO2012- 31358 (first author) and ECO2014-57442-P (second author) We acknowledge research funding from the Spanish Ministry of Finance and Competitiveness, Grant Nos. ECO2012-31358 (first author) and ECO2014-57442-P (second author).

In an effort to meet its obligations under the Kyoto Protocol, in 2005 the European Union introduced a cap-and-trade scheme where mandated installations are allocated permits to emit CO2. Financial markets have developed that allow companies to trade these carbon permits. For the EU to achieve reductions in CO2 emissions at a minimum cost, it is necessary that companies make appropriate investments and policymakers design optimal policies. In an effort to clarify the workings of the carbon market, several recent papers have attempted to statistically model it. However, the European carbon market (EU ETS) has many institutional features that potentially impact on daily carbon prices (and associated ?nancial futures). As a consequence, the carbon market has properties that are quite different from conventional financial assets traded in mature markets. In this paper, we use dynamic modelaveraging (DMA) in order to forecast in this newly-developing market. DMA is a recently-developed statistical method which has three advantages over conventional approaches. First, it allows the coe¢ cients on the predictors in a forecasting model to change over time. Second, it allows for the entire forecasting model to change over time. Third, it surmounts statistical problems which arise from the large number of potential predictors that can explain carbon prices. Our empirical results indicate that there are both important policy and statistical benefits with our approach. Statistically, we present strong evidence that there is substantial turbulence and change in the EU ETS market, and that DMA can model these features and forecast accurately compared to conventional approaches. From a policy perspective, we discuss the relative and changing role of different price drivers in the EU ETS. Finally, we document the forecast performance of DMA and discuss how this relates to the efficiency and maturity of this market.

This paper investigates the relationship between short term and long term inflation expectations in the US and the UK with a focus on inflation pass through (i.e. how changes in short term expectations affect long term expectations). An econometric methodology is used which allows us to uncover the relationship between inflation pass through and various explanatory variables. We relate our empirical results to theoretical models of anchored, contained and unmoored inflation expectations. For neither country do we find anchored or unmoored inflation expectations. For the US, contained inflation expectations are found. For the UK, our findings are not consistent with the specific model of contained inflation expectations presented here, but are consistent with a more broad view of expectations being constrained by the existence of an inflation target.

Many estimation methods of truncated and censored regression models such as the maximum likelihood and symmetrically censored least squares (SCLS) are sensitive to outliers and data contamination as we document. Therefore, we propose a semipara- metric general trimmed estimator (GTE) of truncated and censored regression, which is highly robust and relatively imprecise. To improve its performance, we also propose data-adaptive and one-step trimmed estimators. We derive the robust and asymptotic properties of all proposed estimators and show that the one-step estimators (e.g., one-step SCLS) are as robust as GTE and are asymptotically equivalent to the original estimator (e.g., SCLS). The infinite-sample properties of existing and proposed estimators are studied by means of Monte Carlo simulations.

This paper uses an estimated model of residential electricity demand to examine the impact of proposed tariff changes on a representative sample of 130 Barbadian households. The estimated equation results suggest that the price elasticities of demand for particular appliances varied significantly, with households that utilize solar water heating being more price elastic than households that utilize air conditioning and electric water heating electric heating. The income effects were, however, statistically insignificant, as they may have been captured by choices of appliances rather than utilisation. The estimated model results were then employed to examine the effect of a proposed change in the tariff structure for electricity in Barbados. The simulated results seem to indicate that changes in the electricity rate structure are likely to have very little impact on households demand for electricity. However, changes in consumption patterns could occur within upper consumption and upper income households.

For the sample of European Union countries, the efficiency of social protection public expenditures in providing income support and diminishing income inequality is assessed using a two-step Data Envelopment Analysis. This paper adds to the literature in three ways. First, for each country, efficiency scores are derived using an input-oriented variable returns to scale model. As expected, the least efficient redistributive policies were found for countries with generous welfare systems. Second, the efficiency scores are calculated for two periods, before and after the recent economic crisis. The results obtained in this stage of the analysis highlighted the negative impact of the crisis on social protection public expenditure efficiency. Third, other non-discretionary determinants of social protection public expenditures were highlighted as well, using a censored normal Tobit estimation and an additional OLS estimation. The results were robust to the method of estimation and pointed out that higher efficiency scores are associated with higher employment rates and lower dependency ratios.

Traitement econometrique des reponses protestataires en nombre limite dans les etudes de dispositions a payer : une application en santeDans les etudes d’evaluation contingente, de nombreuses reponses correspondent a des dispositions a payer nulles (DAP), mais avec des justifications fort differentes, qui vont des vraies reponses nulles coherentes avec les decisions economiques aux reponses protestataires. La litterature empirique portant sur les determinants des DAP issues d’encheres a mis en evidence que le modele “double-hurdle” etait le plus approprie pour tenir compte du double caractere de ces reponses nulles. Cependant, quand le nombre de reponses protestataires est trop faible pour etre explicitement modelise, cette approche n’est pas applicable. Ce papier discute des strategies econometriques possibles dans de tels cas, frequents dans les etudes de soins de sante. Les differents modeles envisages sont appliques a l’etude des determinants des DAP, de patients francais atteints du cancer, pour la transfusion sanguine a domicile. Nos resultats montrent que les reponses protestataires ne doivent pas etre eliminees, meme si elles sont en nombre limite, et que le Tobit type II et le modele standard de regression tronquee peuvent tous les deux etre appliques. Toutefois, comme sur echantillons finis de petite taille, la methode d’estimation la plus robuste est celle du bootstrap avec un grand nombre de replications, le modele tronque, facilement applicable, econome en temps de calcul et non sujet aux problemes d’identification dans ce cas contrairement au Tobit type II, est un modele econometrique qui pourrait etre privilegie dans de nombreuses etudes de DAP en economie de la sante.Classification JEL : I18, C13, C24.

This paper assesses the relative efficiency of knowledge production in the OECD using a nonparametric DEA approach. In general, resources allocated to R&D are limited and therefore must be used efficiently, given the institutional and legal constraints. The efficiency scores presented are based on an intertemporal frontier estimation for the period 1995 to 2004. We analyse the impact of the regulatory environment using a single bootstrap procedure. The empirical evidence supports our hypothesis that barriers to entry aimed at reducing competition actually lower R&D efficiency by attenuating the incentives to innovate and to allocate resources efficiently. Copyright 2012 Oxford University Press 2011 All rights reserved, Oxford University Press.

We investigate the finite sample performance of several estimators proposed for the panel data Tobit regression model with individual effects, including Honor¨¦ estimator, Hansen¡¯s best two-step GMM estimator, the continuously updating GMM estimator, and the empirical likelihood estimator (ELE). The latter three estimators are based on more conditional moment restrictions than the Honor¨¦ estimator, and consequently are more efficient in large samples. Although the latter three estimators are asymptotically equivalent, the last two have better finite sample performance. However, our simulation reveals that the continuously updating GMM estimator performs no better, and in most cases is worse than Honor¨¦ estimator in small samples. The reason for this finding is that the latter three estimators are based on more moment restrictions that require discarding observations. In our designs, about seventy percent of observations are discarded. The insufficiently few number of observations leads to an imprecise weighted matrix estimate, which in turn leads to unreliable estimates. This study calls for an alternative estimation method that does not rely on trimming for finite sample panel data censored regression model.

The paper examines factors affecting the households’ expenditure on food away from home in Bangkok area. In this paper, the expenditure is the proportion between the total household expenditure on food away from home and the total household income. The data are from the Household Socio-economic Survey Data in 2009 collected by the National Statistical Office. In total, the data set covers about 2,502 sample households in Bangkok and is analyzed by tobit model. The results show that the average household expenditure on food away from home to the total household income is 0.12. The age of household head, total household income, household size, tenure of residence, household head’s marital status and occupation are the factors affecting the expenditure. Gender of household head, period of education of household head, type of residence, household debt and household head’s hours of participation in the workforce have no influence on the expenditure. The results indicate that the food business in Bangkok area still has a good opportunity for growth because households’ expenditure on food away from home is increasing.

This paper studies the technical efficiencies of the textile manufacturing industries in Pakistan using 5-digit level industry data. Technical efficiencies are computed by the Data Envelopment Analysis technique assuming constant as well as variable returns to scale. The efficiency scores thus obtained are analysed by the TOBIT regression technique to determine how input composition influences these efficiency scores. It is found that imported raw material and machinery exercises a positive effect, whereas non-industrial costs affect technical efficiencies in a negative way. Electricity does not play its due role in affecting technical efficiencies. JEL Classification: C24, D24, L6, O14 Keywords: Technical Efficiency, Data Envelopment Analysis, TOBIT Analysis, Manufacturing Industries

Este trabajo proporciona evidencia empírica en cuanto a los salarios de los inmigrantes en España y ofrece una medida de la discriminación de este grupo en comparación con los asalariados nativos. En base a los datos de la Muestra Continua de Vidas Laborales (MCVL), que permite el análisis de distintos subgrupos de la población extranjera (por región de procedencia, Comunidad en la que trabajan, etc.), se estiman ecuaciones de ganancias para nativos e inmigrantes, utilizando modelos Tobit. Posteriormente, se usan tales resultados para estudiar la distribución de los diferenciales salariales entre españoles e inmigrantes, adaptando la metodología de Jenkins (1994).

The article summarizes the key results of researches in the field of early warning systems for financial crises, conducted by the Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF) since 2005. The proposed early warning system consists of three major blocks: the leading indicators of certain types of risks and the composite leading indicator of a systemic banking crisis; the medium-term scenario forecasting of key macroeconomic and financial indicators; stress testing of credit and liquidity risks of banks. On the basis of this early warning system we estimate the risks of financial crisis and some kinds of systemic risks in the different scenarios for the Russian economy in 2012. The analysis, in particular, revealed a sensitivity threshold of the domestic financial sector to changes in the world oil prices. Furthermore, it was found that the greatest destabilizing effect on the Russian financial sector may be caused by systemic credit risk.

The paper analyzes empirically, in Romania’s case, the relationship between economic development (dependent variable) and its political factors (independent variables). The analysis is based on the construction of a linear “Logit Model” and the data set is covering the period 1926- 2007. The main results show that, in Romania’s case, which the economy has an expansive and competitive market, the economic development, can be accompanied, by high levels of democratization, with high political stability, on a republican base, but this is not a rule.

This paper discusses the extent and the determinants of the internationalization of European inventive activity, between 1990 and 2004, using an innovative method to treat the information contained in the European Patent Office's Patstat database. The observed level of internationalization of inventive activities, while being rather low, has steadily increased over time. The amount of collaboration between actors residing in different countries is assessed by means of a "gravity model", as it is familiar in the literature on international trade. The amount of bilateral collaboration is positively affected by the presence of a common language and a common border, and by the common participation in the European Union. Participation in the Euro Zone is also found to have a (marginally) negative effect. International collaboration is negatively affected by distance, with estimated elasticities that are significantly smaller than the ones that characterize international trade. Contrary to the rumors about the "death of distance", this effect has become stronger in recent years.

We examine the use of the likelihood ratio (LR) statistic to test for unobserved heterogeneity in duration models, based on mixtures of exponential or Weibull distributions. We consider both the uncensored and censored duration cases. The asymptotic null distribution of the LR test statistic is not the standard chi-square, as the standard regularity conditions do not hold. Instead, there is a nuisance parameter identified only under the alternative, and a null parameter value on the boundary of the parameter space, as in Cho and White (2007a) . We accommodate these and provide methods delivering consistent asymptotic critical values. We conduct a number of Monte Carlo simulations, comparing the level and power of the LR test statistic to an information matrix (IM) test due to Chesher (1984) and Lagrange multiplier (LM) tests of Kiefer (1985) and Sharma (1987) . Our simulations show that the LR test statistic generally outperforms the IM and LM tests. We also revisit the work of van den Berg and Ridder (1998) on unemployment durations and of Ghysels et al. (2004) on interarrival times between stock trades, and, as it turns out, affirm their original informal inferences.

This paper uses a unique and recently available dataset that contains detailed information on firms from around the world to investigate factors that affect under-reporting behaviour by firms. The empirical strategy employed exploits the nature of the dependent variable, which is interval coded, and uses interval regression which provides an asymptotically more efficient estimator than the ordered probit, provided that the classical linear model assumptions hold. These assumptions are investigated using standard diagnostic tests that have been modified for the interval regression model. Evidence is presented that shows that firms in all regions around the world engage in under-reporting. Regression results indicate that government corruption has the single largest causal effect on under-reporting, resulting in the percentage of sales not reported to the tax authority being 53.4 percent higher. Taxes have the second single largest causal effect on under-reporting, resulting in the percentage of sales not reported to the tax authority being 20.2 percent higher. Access to financing, organized crime, political instability and the fairness of the legal system were found to have no effect on under-reporting. It is also found that there is a significant correlation between under-reporting and the legal organization of the business, size, age, ownership, competition and audit controls.

In this paper is performed an econometric analysis of the dependence between of consumption, GDP and interest rates of 15 European Union countries over a period of three years. The main purpose of this paper is to show how this can be done using the Eviews program, the steps that we must go through this program and to forecast achievements of the phenomenon studied.

This paper addresses the impact of addiction and social interactions on cigarette demand, controlling for demographic and socioeconomic factors. A Box-Cox double-hurdle model for the simultaneous decisions of how much to smoke and whether to quit smoking is estimated on individual data from the 2000 Italian “Health Status and Use of Health Services” survey. The model incorporates the fixed costs of quitting and allows for the analysis of the effects of addiction and within-household interactions on smoking participation and cigarette consumption. Estimation results show that the duration of the smoking habit, used as measure of addiction, significantly increases the level of cigarette consumption and lowers the probability of quitting. Within-household social interactions affect individual’s attitude toward smoking. Participation decision is significantly influenced by the presence of other smokers and individual cigarette consumption increases as the consumption of the peer-group grows. Finally, gender differences are formally tested to verify whether male and female sub-samples can be pooled or should be separately analyzed. The hypothesis of equal consumption parameters is clearly rejected, suggesting the opportunity of distinguishing the consumption patterns of men and women.

High-breakdown-point regression estimators protect against large errors and data contamination. We generalize the concept of trimming used by many of these robust estimators, such as the least trimmed squares and maximum trimmed likelihood, and propose a general trimmed estimator, which renders robust estimators applicable far beyond the standard (non)linear regression models. We derive here the consistency and asymptotic distribution of the proposed general trimmed estimator under mild β-mixing conditions and demonstrate its applicability in nonlinear regression and limited dependent variable models.

Economic theory assigns a central role to risk preferences. This article develops a measure of relative risk tolerance using responses to hypothetical income gambles in the Health and Retirement Study. In contrast to most survey measures that produce an ordinal metric, this article shows how to construct a cardinal proxy for the risk tolerance of each survey respondent. The article also shows how to account for measurement error in estimating this proxy and how to obtain consistent regression estimates despite the measurement error. The risk tolerance proxy is shown to explain differences in asset allocation across households.

The focus of this paper is the subjective welfare of the individual in the case of Croatia, a country that in the 1990s carried out a transformation from a socialist to a market-based economy while being at war as a result of the break-up of the former Yugoslavia. Subjective welfare is commonly found to be different from welfare as measured by objective criteria such as income. This difference is first explored by profiling poverty based on the two measures, and here the largest difference is found among those who are not objectively poor. Further the determinants of subjective welfare are analyzed in an ordered probit model broadly grouped as objective variables of personal or household circumstances, and measures of relative income, individual income compared with different reference groups. The results show that, apart from absolute income, which leaves large room for other explanations, relative income is the strongest determinant. This can be connected to the transition heritage of Croatia and is also in line with what has been found in other countries.

Este artículo estima la tasa de retorno de la educación de la población asalariada en Bogotá para 1997 y 2003 teniendo como referencia la teoría del capital humano. Para la estimación se corrige el sesgo de selección por medio de la metodología de Heckman (1979). A diferencia de estudios anteriores, que usan la Encuesta Nacional de Hogares, en éste se utiliza la información disponible en la Encuesta de Calidad de Vida que también es representativa para Bogotá. Se encuentra que los retornos de la educación y de la experiencia potencial, así como la elasticidad horas-ingreso laboral y el ingreso laboral se reducen en el periodo posterior a la recesión económica. Palabras clave: ecuación de Mincer, retorno de la educación, sesgo de selección, teoría del capital humano. Clasificación JEL: C24, J31, J24, J38. Abstract: This paper estimates the returns to education in Bogotá in 1997 and 2003 by means of Heckman’s maximum likelihood methodology. The analytical framework used is Human Capital Theory. Instead of using the ‘Encuesta Nacional de Hogares’ (National Household Survey), as does current literature, we use the ‘Encuesta de Calidad de Vida’ (Life Quality Survey). We found a reduction after the economic recession (1999) in aspects such as the returns to education and the impact of experience in Bogotá between these years. There are also suggestions about a decrease in the labor income and in the hour-income elasticity. Keywords: Mincer equation, returns to education, selection bias, human capital theory. JEL classification: C24, J31, J24, J38. Résumé: Cet article calcule le taux de rendement de l’éducation sur le salariat dans la ville de Bogotà entre 1993 et 2003 dans le cadre de la théorie du capital humain. Pour ce faire, nous utilisons la méthodologie proposée par Heckman (1979) qui permet de corriger les biais de sélection. Nous utilisons les données disponibles dans l’Enquête de Qualité de Vie au lieu de l’Enquête Nationale pour les Foyers, les deux enquêtes étant significatives pour la ville de Bogotà. Nous montrons que les taux de rendement de l’éducation et de l’expérience potentielle ainsi que l’élasticité heurs-revenu du travail et le revenu du travail, se réduisent pendant la période qui a suivi la récession économique. Mots clés: équation de Mincer, rendement dans l’éducation, biais de sélection, théorie du capital humain. Classification JEL: C24, J31, J24, J38.

We introduce a new time series model that can capture the properties of data as is typically exemplified by monthly US unemployment data. These data show the familiar nonlinear features, with steeper increases in unem- ployment during economic downswings than the decreases during economic prosperity. At the same time, the levels of unemployment in each of the two states do not seem fixed, nor are the transition periods abrupt. Finally, our model should generate out-of-sample forecasts that mimic the in-sample properties. We demonstrate that our new and flexible model covers all those features, and our illustration to monthly US unemployment data shows its merits, both in and out of sample.

This paper investigates the association between personality traits and charitable behaviour, namely donations of time and money, using data from Understanding Society, the most recent large scale UK household longitudinal survey. Due to the censored nature of the outcome variables, i.e. some individuals do not engage in charitable behaviour, we employ censored quantile regression models. Personality traits are classified according to the 'Big Five' taxonomy: openness to experience; conscientiousness; extraversion; agreeableness; and neuroticism. The quantile approach allows us to explore the effect of personality traits across the entire distribution of charitable behaviour rather than just at the mean, which has generally been the case in the existing literature. In general, after conditioning on an extensive set of controls, conscientiousness and neuroticism are found to be inversely related to donating time and money, whilst openness to experience, which has a positive effect, is the dominant trait in terms of magnitude. Interestingly, personality traits are found to have a stronger association with donations of time and money at the extreme points of the distribution of donations relative to that at the median, thereby highlighting the additional information revealed by quantile approach.

Panel surveys offer a valuable tool for researchers to explore the dynamics underlying individual and household behaviours. The Achilles heel of panel data is attrition. This paper examines the determinants and implications of attrition in the first two waves of South Africa's National Income Dynamics Survey (NIDS). Multivariate tests in labour market and health specifications show that there is some moderate evidence of attrition bias in estimated coefficients based on the non-attriting sample. This bias can be seen in labour market specifications, in particular for men, and for Africans, and to a much lesser degree in health specifications, in particular for small samples of Whites. Researchers should take care when using the panel data set to generalise to the overall population.