Showing papers on "Tobit model published in 2011"

Do Financial Constraints Matter for Foreign Market Entry? A Firm-level Examination

Abstract: Recent theoretical and empirical contributions stress the importance of financial development for international trade. This paper investigates whether financial constraints matter for foreign market entry at the firm level using dynamic panel data techniques. Dynamic Probit and Tobit models that account for state dependence and unobserved heterogeneity are used to analyse the effect of financial indicators on export activities. The empirical framework tests for heterogeneous effects among different quartiles of the size and productivity distribution, across previous exporters and potential starters, and across different types of industries as those are predicted by theoretical models. The empirical analysis is applied to a large panel dataset of French manufacturing firms over the years 1998–2005. The data contain a high share of small firms that are usually the most likely to be financially constrained. Although financial indicators are significantly correlated with export status and export share, there is no evidence that financial constraints have a direct impact on foreign market participation or sales in foreign markets once observed and unobserved firm heterogeneity is controlled for. This result is robust to using alternative estimation techniques and also holds for subgroups of firms that are more likely to face financial constraints and industries that are more dependent on financial factors.

Structural Agricultural Land Use Modeling for Spatial Agro-Environmental Policy Analysis

Abstract: This paper develops a spatially disaggregated, structural econometric model of agricultural land use and production based on the joint multi-output technology representation introduced by Chambers and Just (1989). Starting from a flexible specification of the farm profit function, we derive land use allocation, input application, crop yield, and livestock intensity equations in a joint and theoretically consistent framework. To account for the presence of censored observations in micro-level data, the model is estimated as a system of two-limit Tobit equations via quasi-maximum likelihood. We present an empirical application using fine-scale spatial data covering the entirety of England and Wales and including the main economic, policy, and environmental drivers of land use change in the past forty years. A simulation of the effects of diffuse pollution reduction measures illustrates how our approach can be applied for agro-environmental policy appraisal.

Assessing health efficiency across countries with a two-step and bootstrap analysis

Abstract: Regressing Data Envelopment Analysis (DEA) output efficiency scores on nondiscretionary variables, with a two-stage DEA/Tobit and bootstrap procedures, we show that health inefficiency in Organization for Economic Co-operation and Development (OECD) countries is related to Gross Domestic Product (GDP) per head, education level, obesity and smoking habits.

A panel data modelling of international tourism demand: evidences for romania

Abstract: This paper analysis the determinants of international tourism demand for Romania and it quantifies their influences. The authors elaborate two models, a fixed-effects model and the Tobit model, to estimate tourist inflow data from twenty-three European countries, for the period 1997-2008. In the fixed effects static panel model, we find that GDP per capita, bilateral trade, population, prices are the main determinants of tourism flows to Romania. For the Tobit model, all the variables taken into consideration, GDP per capita, bilateral trade, population, geographical distance, prices are influencing the international tourism demand. Both models indicate that trade, population, and income are more important determinants than relative prices or geographical distance between Romania and countries of origin.

An analysis of tourists' expenditure on winter sports events through the tobit censorate model.

Abstract: This study analyses the economic impact of the Biathlon World Cup 2009 in Antholz-Anterselva. The survey concentrates on the immediate, direct and short-term additional revenue brought into the region by foreign sports event spectators. The authors first apply an expenditure-based segmentation technique to data collected during the event to separate respondents according to socio-demographic variables. Second, a Tobit analysis is applied to obtain an expenditure model that is useful in explaining the different determinants of trip expenditures by spectators of the event. The results reveal significant socio-demographic differences between the four expenditure groups. For instance, heavy spenders are composed mainly of mature tourists, arriving for the first time in medium-sized groups. Also, the most important factors in total expenditure are income level, the geographical origin of the spectator and the size of the travel group.

Estimating the Environmental Impact of Land and Production Decisions with Multivariate Selection Rules and Panel Data

Abstract: We propose an estimation procedure dealing with multivariate selection and dynamics in land choice and unobserved heterogeneity in structural and crop selection equations. The method is applied to a multi-output profit function with multiple corner solutions and farm-level panel data. Estimation results reveal that the single selection rule associated with the Tobit procedure is rejected in favor of our multivariate selection treatment. Inconsistent estimates are expected with the Tobit procedure, or if farmer fixed effects are omitted, which can have important consequences for policy recommendations, as illustrated in an evaluation of nitrogen runoff elasticities with respect to economic variables. Copyright 2011, Oxford University Press.

Comparisons of Tobit, Linear, and Poisson-Gamma Regression Models : An Application of Time Use Data

Abstract: Time use data (TUD) are distinctive, being episodic in nature and consisting of both continuous and discrete (exact zeros) values. TUD is non-negative and generally right skewed. To analyze such da...

Simulation estimation of two‐tiered dynamic panel Tobit models with an application to the labor supply of married women

Abstract: In this paper a computationally practical simulation estimator is proposed for the two-tiered dynamic panel Tobit model originally developed by Cragg (1971). The log-likelihood function simulated through procedures based on a recursive algorithm formulated by the Geweke–Hajivassiliou–Keane simulator is maximized. The simulation estimators are then applied to study the labor supply of married women. The rich dynamic structure of the labor force participation decision as well as hours worked decisions that are conditional on the participation of married women are identified by using the proposed simulation estimators. The average partial effects of the participation and hours worked decisions for married women in response to fertility decisions and increases in the husband's income are also investigated. It is found that the hypothesis that the fertility decision is exogenous and the hypothesis that the husband's income is exogenous to married women's labor supply function are both rejected in the dynamic and static two-tiered models. Moreover, children aged between 6 and 13 years old may have a negative impact on the hours worked decision for married women that is conditional on their participation. However, these children may provide some positive incentives for married women to participate in the labor force. Copyright © 2009 John Wiley & Sons, Ltd.

Dynamic Censored Regression and the Open Market Desk Reaction Function

Abstract: The censored regression model and the Tobit model are standard tools in econometrics. This paper provides a formal asymptotic theory for dynamic time series censored regression when lags of the dependent variable have been included among the regressors. The central analytical challenge is to prove that the dynamic censored regression model satisfies stationarity and weak dependence properties if a condition on the lag polynomial holds. We show the formal asymptotic correctness of conditional maximum likelihood estimation of the dynamic Tobit model, and the correctness of Powell’s least absolute deviations procedure for the estimation of the dynamic censored regression model. The paper is concluded with an application of the dynamic censored regression methodology to temporary purchases of the Open Market Desk. This article has supplementary material online.

Calculating utility decrements associated with an adverse event: marginal Tobit and CLAD coefficients should be used with caution.

Abstract: Background: When calculating the decreases in health utility associated with adverse events, often a number ofrespondents achieve the upper utility bound of 1. “Marginal” Tobit or CLAD coefficients...

Use of virtual index for measuring efficiency of innovation systems: A cross-country study

Abstract: In this study we propose a virtual index for measuring the relative innovativeness of countries. Using a multistage virtual benchmarking process, the best and rational benchmark is extracted for inefficient ISs. Furthermore, Tobit and Ordinary Least Squares (OLS) regression models are used to investigate the likelihood of changes in inefficiencies by investigating country-specific factors. The empirical results relating to the virtual benchmarking process suggest that the OLS regression model would better explain changes in the performance of innovation- inefficient countries.

Gender differences in remittance behavior: evidence from vietnam

Abstract: This paper investigates the role of gender in remittance behavior among migrants using the 2004 Vietnam Migration Survey data. The gender dimension to remittance behavior has not featured strongly in the existing literature and our findings thus contain novel appeal. In addition, we use estimates from both homoscedastic and heteroscedastic tobit models to decompose the raw gender difference in remittances into treatment and endowment components. We find little evidence that gender differences in remittances are attributable to behavioral differences between men and women, and this finding is invariant to whether the homoscedastic or heteroscedastic tobit is used in estimation.

Measuring the effect of transaction costs for investment in irrigation pumps: application of the unobserved stochastic threshold model to the case of Nigeria.

Abstract: This article empirically assesses the effect of unobserved transaction costs for Nigerian farmers when investing in irrigation pumps The unobserved stochastic threshold (UST) model popularly used in labor economics literature is applied, and is compared with two models, the Tobit and the Heckman sample selection model, which are slightly more restrictive versions of the UST model The results indicate that the unobserved transaction costs are higher for female farmers, landless farmers, those who have a comparatively high dependency ratio, and those who live far from town The results suggest that the unobserved transaction costs can be as important as the factors determining the profitability of irrigation pumps, which emphasizes the importance of reducing transaction costs and providing the environment for higher returns from investment in irrigation From a methodological perspective, the UST model is found to be more accurate and informative than the Tobit and Heckman models

On alternative methods for measuring visual field decay: Tobit linear regression.

Abstract: We read with interest the article by Caprioli et al. in the June 2011 issue. In this article, the authors propose a novel method of measuring and predicting the rate of visual field (VF) decay in glaucoma patients. This is an important and clinically relevant topic. Of particular interest was the authors’ application of an exponential fit for threshold sensitivity (in decibels) against time, which was found to be the best-fitting model compared against a linear and a quadratic regression—according to the Akaike information criterion (AIC)—in 96.8% of the 21,006 of the data series investigated. This contradicts the idea that point-wise VF decay is best modeled and predicted using simple ordinary least-squares linear regression (OLSLR); previous research investigating other more complex models has shown these to be less accurate than OLSLR for predicting VF progression. In response to this article, we would like to suggest possible statistical reasons why the exponential regression is shown to be a better-fitting model than simple OLSLR. Standard VF threshold measurements from the Humphrey Visual Field Analyzer (Carl Zeiss Meditec, Dublin, CA) are limited to the range of 0 to 50 dB. Consequently, VF thresholds are vulnerable to floor (left-censoring) and ceiling (right-censoring) effects. Caprioli et al. state that “exponential fits for individual locations seem to work well for advanced damage because values usually approach 0 dB in an asymptotic fashion”; conversely, we argue that VF progression may occur linearly throughout the disease but the exponential model is more robust than OLSLR to the floor effects of VF threshold data. Floor effects are pertinent to the VF data investigated by Caprioli et al., since the models were applied to patients with moderate to advanced glaucomatous damage. Furthermore, in Figure 9 of their study, it is apparent that for “actual thresholds” above approximately 20 dB, the predicted thresholds from the exponential regression greatly underestimate the VF thresholds. In circumstances in which the dependent variable is censored (such as threshold sensitivity), the assumptions of the OLSLR model are not strictly valid. However, there are statistical prescriptions that may provide a solution. The Tobit linear regression model employs a latent (unobservable) dependent variable that respects leftand/or right-censoring and predicts this variable only within the specified range. To illustrate the usefulness of Tobit regression as well as support the hypothesis that VF progression may occur linearly, even in advanced disease, we synthetically created the example shown in Figure 1, which is akin to Figure 2 in Caprioli et al. The Tobit linear regression model is fitted to the synthetic data in Figure 1 (blue line) and compared with the exponential regression (red line) and OLSLR (black line). Different models can be contrasted using the AIC, with the lowest AIC indicating the best model. Specifying appropriate candidate models is imperative, because if only poor models are compared, then the AIC will simply select the best of a bad bunch. Models can be further evaluated using the formula:

Joint modelling of survival and cognitive decline in the Australian Longitudinal Study of Ageing

Abstract: Summary. The paper describes the use of a longitudinal tobit model to characterize cognitive decline over a 13-year period in a cohort of 2087 elderly Australians. Use of a tobit formulation allows for the so-called ‘ceiling effect’ wherein many subjects achieve perfect test scores. A Bayesian hierarchical joint model is presented that allows for random subject-specific intercepts and slopes, as well as for informative dropout. Results suggest several potential areas of intervention. For example, there is a clear dose–response effect of exercise whereby increasing levels of exercise are associated with higher cognitive scores.

Economic Valuation of Private Sector Waste Management Services

Abstract: This paper reports a study regarding households’ willingness to pay for private sector solid waste management services. The data originated from a contingent valuation survey conducted in 224 households in Ilorin in southwest Nigeria and was analysed using tobit and censored least absolute deviations models. The use of a robust and consistent estimator to model zero willingness to pay responses was discussed. The results show that the respondents were willing to pay more than one percent of their household income per year. Their willingness to pay amount was influenced by income, education, activities of sanitary inspectors, house type and occupation. The censored least absolute deviations model outperformed the tobit model. We suggest that government agencies should be actively involved in monitoring activities of private firms regarding provision of waste management services. The findings from this study can help policy-makers in designing a more sustainable waste management strategy in southwest Nigeria, as well as in other developing countries.

The cost efficiency of Greek cooperative banks: an application of two-stage data envelopment analysis

Abstract: This study aims to assess the Cost Efficiency (CE) of the Greek cooperative banks over the period 2000?2005. We first use Data Envelopment Analysis (DEA) to estimate the technical, allocative and cost efficiency for each bank in sample. Then, we use a bootstrapping censored (Tobit) regression approach to determine whether and how internal and external factors influence banks' efficiency. The results of DEA indicate that Greek cooperative banks could improve their cost efficiency by 18.4% on average as well as that the dominant source of cost inefficiency is allocative rather than technical. The results of the second-stage regression indicate that bank total assets and the equity to assets ratio, as well as the GDP per capita and the unemployment rate in the region influence efficiency; however, their impact is not robust across different efficiency measures.

Comparing technical efficiency of organic and conventional coffee farms in Nepal using data envelopment analysis (DEA) approach

Abstract: Data Envelopment Analysis (DEA) approach used to estimate technical efficiency and followed by regressing the technical efficiency scores to farm specific characters under tobit regression model. Primary data was collected from random samples of 240 (120 from each) coffee famers. Mean technical efficiency score was 0.89 and 0.83 in organic and conventional coffee farming respectively. Farms operating under CRS, DRS and IRS were 31.67, 3.83 and 37.5% respectively in organic coffee and 29.17, 25 and 45.83% respectively in conventional farming areas. Tobit regression showed the variation in technical efficiency was related education, farm experience and training/extension services and excess to credit.

Efficiency and Heterogeneity of Public Spending in Education Among Italian Regions

Abstract: The Italian educational system is strictly regulated by the Ministry of Education. However, there are strong differences in educational inputs and outputs among Regions, as can be noticed by analyzing the allocation of public budgets to the Regions and their students' (average) performance in national and international test scores. A general institutional change is ongoing in Italy, that is, the decentralization of competencies from the State to the Regions (federalism). Some insights are necessary about the efficiency of public spending on education in a comparative perspective across Regions. To estimate efficiency scores, a non-parametric technique called DEA (Data Envelopment Analysis) was used. The unit of analysis are the 18 Italian Regions, with the focus on the lower- secondary education. Then a second-stage Tobit regression was used to detect the factors affecting efficiency. The results corroborate the difference between the North and South of Italy (the Regions in the North outperform their counterparts in the South). When looking at the Regional socio-economic context, GDP per capita appears as the key determinant of efficiency.

Analysis of non-ignorable missing and left-censored longitudinal data using a weighted random effects tobit model

Abstract: In a longitudinal study with response data collected during a hospital stay, observations may be missing because of the subject's discharge from the hospital prior to completion of the study or the death of the subject, resulting in non-ignorable missing data. In addition to non-ignorable missingness, there is left-censoring in the response measurements because of the inherent limit of detection. For analyzing non-ignorable missing and left-censored longitudinal data, we have proposed to extend the theory of random effects tobit regression model to weighted random effects tobit regression model. The weights are computed on the basis of inverse probability weighted augmented methodology. An extensive simulation study was performed to compare the performance of the proposed model with a number of competitive models. The simulation study shows that the estimates are consistent and that the root mean square errors of the estimates are minimal for the use of augmented inverse probability weights in the random effects tobit model. The proposed method is also applied to the non-ignorable missing and left-censored interleukin-6 biomarker data obtained from the Genetic and Inflammatory Markers of Sepsis study.

Tobit model for outcome variable is limited by censoring in nursing research.

Abstract: Background In nursing research, censoring may limit the outcome variable of interest. Well-known examples reflect the so-called floor or ceiling effect. Offering a biased estimator of the limited data, the linear regression model with ordinary least-squares estimation is one of the most frequently used methods. This method requires an innovative approach. Objectives The aims of this study were to (a) introduce an alternative data analysis approach (Tobit model), (b) discuss the constraints of ordinary least-squares regression and complementary advantages of the Tobit model in working with censoring data, and (c) provide a fundamental understanding of the Tobit model in the nursing and healthcare domains. Method The benefits of the Tobit model are outlined using an example of activities of daily living. Results Based on model-fit parameters, residual plots, regression coefficients, and significance levels, the results indicate that the Tobit model performs more accurately than an ordinary least-squares regression when data are subject to a ceiling or floor effect. Conclusion When the Tobit model is specified correctly, it allows nursing researchers to ameliorate biased coefficient estimates occurring when health status measures are subject to limited data by censoring. Despite the theoretical superiority of the Tobit model to classical statistical data analysis, nurse researchers are cautioned to be aware of the limitations and appropriate applications associated with the Tobit model.

An application of the two-stage Bivariate Probit-Tobit model to corporate financing decisions

Abstract: Most of the previous studies on the firms’ debt-equity choice utilize the standard single equation Probit (or Logit) model as if firms face a single dichotomous decision to issue debt or equity, but not both. The main purpose of this study is to use a two stage Bivariate Probit–Tobit model to examine the factors affecting the choice between internal and external funding and between debt and equity as well as the size of issues. Our results indicate that the Bivariate-Probit estimation is more efficient than that of two independent Probit equations. An examination of factors that affect the choice of financing form and the size of issue support the predictions of trade-off theory. The pecking order’s prediction that, if external funding is needed, firms issue debt first and then equity finds no support in this study as firms with higher information asymmetry have propensity to issue equity rather than debt. While information asymmetry affects the choice between debt and equity, we find no evidence that it influences the size of issue.

Testing Household Economies of Scale in Uzbekistan

Abstract: This paper investigates empirically the relationship between household economies of scale and consumption in Uzbekistan. Particular attention is paid to the so-called “zero consumption problem” and Tobit estimator is utilized to deal with the problem. Using the household survey dataset made available recently, we test presence (or lack) of household economies of scale in seven different consumption categories (food, meals out, clothing, education, health, transportation and shelter). We find evidence of strong and positive household economies of scale in consumption of meals out, clothing, education, health, transportation and shelter, while consumption of food fails to indicate this pattern. We also estimate food Engel curve using non-parametric kernel estimates and fail to find the existence of household economies of scale through food consumption data.

What Motivates Gifts? Intra-Family Transfers in Rural Malawi

Abstract: This paper uses Family Transfers Project data collected in rural Malawi during 1999 to ascertain the motivation for gift-giving using discriminating hypotheses. The study models monetary and monetized gifts sent and received between the survey respondents and their parents, their children, and their siblings as a function of sender and receiver characteristics. Individual analyses are compared with household level models to reveal that both individual and household characteristics can matter in different cases. OLS, Probit and Tobit models are compared to conclude that, as with other similar studies, a wide range of motivations exist including altruism, (co-)insurance, and an inheritance motive. Motivations differ slightly depending upon the relationship between the sender and receiver, however, no single motive can be attributed to any given relationship.

Determinants of Farmers’ Access to Micro-Credit in Oyo State, Nigeria

Abstract: This study investigated access of farmers to credit in Oyo State, Southwest, Nigeria . Eight(8) communities, (2 from 4 Local Government Areas in each agricultural zone) were selected. 240 respondents (30/community) were sampled using 3-stage stratified random sampling technique. Both primary (using interview guides) and secondary data were collected. Apart from descriptive statistics and the Z-score test of significance, Tobit regression model was used to capture the expected dichotomous responses of respondents, and the determinants of their access to the credit in the study area. The study revealed that, most of the respondents (82.4%) were found between the active productive ages of 25 and 55 years in the study area, with the mean age found to be 43.2 years. About 76.2% are married. Mean household size is 8 persons. Farming as the major occupation was dominated by 48.8% of crop farmers. Though 53.3% had no formal education, 45.9% had attended Primary school education Years of farming experience in the area ranged from 5-42 years with the modal class between 21 and 30 years. Result of the Tobit probability regression analysis also revealed that age(X 1 ),education(X 4 ),land ownership(X 9 ),Income(X 11 ) and value of Assets(X 12 ) were all found to be significant p ≥ 0.01 while marital status(X 3 ), farming experience(X 5 ), existence of Credit Institutions in the area(X 7 ) were significant at p ≥ 0.05), to access to credit in the study area. All the significant variables except Age (X 1 ) were positively correlated to access to credit. Adjusted R 2 was 0.876. It was concluded that policies be redirected on government-sponsored and guaranteed micro-credit financing schemes that could favour the small holder farmers who are the major producers of food and fibre in Nigeria particularly in the study area. The need for rural credit scheme to be expanded in terms of scope and geographical coverage, promote the awareness of rural banking culture, organize farmers into formidable cooperatives to facilitate access to credit, strengthen credit policies and redefine Small and Medium Scale Enterprises and Investment Scheme(SMEIS) to become better focused were therefore recommended. Keywords: Access, Micro-credit, credit sources, Farmers, Oyo State, southwest Nigeria