Tobit Estimation Research Articles

The influence of industry affiliation on corporate tax avoidance in Malaysia

Prior studies on tax avoidance have been emphasising on the individuals behaviour rather than corporations. In addition to this, the available studies on corporate tax avoidance, to date, have been focusing on the developed market while very little attention has been given to the developing countries. Thus, this study attempts to investigate the corporate tax avoidance behaviour in Malaysia, focusing on industry affiliations. Specifically, the objective of this study is to examine the importance of industry affiliations as possible contributions of corporate tax avoidance mechanism. This study documented the link between industry affiliations and corporate tax avoidance in an emerging market. This study tested the relationship by using a crosssectional-time series valuation using panel data analyses, which is Tobit estimations. The results confirmed the importance of industry differences in explaining corporate tax avoidance activity. As more data become available in the future, one could include tax avoidance study in non-listed companies.

Stadium attendance in German professional football – the (un)importance of uncertainty of outcome reconsidered

Although deeply ingrained in the economics of professional team sports literature, previous research could not confirm the importance of outcome uncertainty in European professional football. Moreover, a negative effect was detected and explained rather controversially: It is argued that the majority of spectators prefer to see the home team play either a much inferior team or a rather successful team. With data of n = 306 matches in the German Bundesliga, a generalized Tobit estimator with individual cut-off points and error terms clustered by home teams is employed to follow up with the discussion on the (un)importance of outcome uncertainty. The results highlight a significant positive effect on attendance when either the home and/or the away team still has a theoretical chance to win the championship while the suggested importance of teams still having the possibility to qualify for the UEFA Champions League is not supported (medium-term uncertainty). Furthermore, in line with previous research we could detect a negative effect of short-term uncertainty. However, while there is no evidence that spectators prefer the home team to play an inferior team, the results suggest that it is rather a strong brand of the away team that rises attendance figures in the German Bundesliga.

Financial Dependence and Aid Allocation by Swiss NGOs: A Panel Tobit Analysis

Aid by nongovernmental organizations (NGOs) is still widely believed to be superior to official development assistance (ODA). However, the incentives of NGOs to excel and target aid to the poor and deserving are increasingly disputed. We contribute to the emerging literature on the allocation of NGO aid by performing panel Tobit estimations for Swiss NGOs. We cover the allocation of both self-financed and officially cofinanced aid for a large panel of NGOs and recipient countries. Furthermore, we offer new insights by classifying each NGO according to its financing structure and by interacting financial dependence with measures of need and merit of recipients as well as aid from other donors. It turns out that the allocation of NGO aid is much in line with that of ODA. This applies particularly to officially refinanced NGOs. Moreover, NGOs tend to locate where their peers are active. However, the poverty orientation of NGOs and their incentives to engage in difficult environments are independent of the degree of official refinancing. The allocation of self-financed aid differs in several important respects from the allocation of officially cofinanced aid.

What do we know about capital structure? Revisiting the impact of debt ratios on some firm-specific factors

We revisit the evidence on the effect of size, tangibility, profitability and growth opportunities on debt ratios using a large sample of the US and the UK firms and applying advanced estimation methods that are perfectly aligned with the panel data. We employ a double-censored Tobit estimator, a Fixed-Effect (FE) estimator, a model that accounts for cross-sectional and time-series dependence and a Fama–Macbeth regression, we find that the signs of size, tangibility, profitability and growth opportunities for the US firms are consistent with previous studies. As with the US evidence we show that size and tangibility are positively associated with leverage whereas profitability and growth opportunities are negatively associated with leverage for the UK firms. However, the impact of growth opportunities on leverage for UK firms is inconclusive. We conclude that size, tangibility, profitability and growth opportunities cannot explain the theoretical aspects of capital structure.

Factors affecting hospital admission and recovery stay duration of in-patient motor victims in Spain

Hospital expenses are a major cost driver of healthcare systems in Europe, with motor injuries being the leading mechanism of hospitalizations. This paper investigates the injury characteristics which explain the hospitalization of victims of traffic accidents that took place in Spain. Using a motor insurance database with 16,081 observations a generalized Tobit regression model is applied to analyse the factors that influence both the likelihood of being admitted to hospital after a motor collision and the length of hospital stay in the event of admission. The consistency of Tobit estimates relies on the normality of perturbation terms. Here a semi-parametric regression model was fitted to test the consistency of estimates, concluding that a normal distribution of errors cannot be rejected. Among other results, it was found that older men with fractures and injuries located in the head and lower torso are more likely to be hospitalized after the collision, and that they also have a longer expected length of hospital recovery stay.

Factors Influencing Consumers’ Financial Transactions in Islamic Banks Compared with Conventional Banks: Empirical Evidence from Selected Middle-East Countries with a Dual Banking System

Abstract Despite various evidences that show Islamic banking has gained popularity even by non-Muslim consumers and businesses in many parts of the world, there is still a general misconception that consumer’s choice for Islamic banking is only influenced by religious obligations and thus it is just a Muslim-only affair. Yet, our knowledge of consumer motivations for choosing Islamic versus conventional banking services is modest and the research to date is limited and ambiguous on these key issues. Therefore, this study conducts a two-step empirical analyses and first identifies the factors influencing customer’s decision whether to choose Islamic or conventional banking using Linear Probability Model (LPM) and Tobit estimation method, and as a second step, it investigates the main attributing factors to consumers overall level of satisfaction with the services provided by Islamic banks compared to conventional banks using ordinal-logistic regression model. The study was based on a randomly selected 322 bank customers from Bahrain, Jordan, and UAE. The study confirms that although religious factors such as Shari’a compliance are important, other non-religious factors including better quality of services and information disclosure are also playing crucial roles for the growing consumers’ demand for Islamic banking. Nevertheless; factors such as better rate of return, accessibility to credit, and SMS banking are found to be the main significant determinants of consumers’ choice and satisfaction with the services provided by conventional banks. Overall, the recent experience especially after the financial crisis of 2008 demonstrates that Islamic banking system can be part of the solution since it is mainly based on stronger regulatory system.

Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold

Claeskens and Hjort (2003) have developed a focused information criterion (FIC) for model selection that selects different models based on different focused functions with those functions tailored to the parameters singled out for interest. Hjort and Claeskens (2003) also have presented model averaging as an alternative to model selection, and suggested a local misspecification framework for studying the limiting distributions and asymptotic risk properties of post-model selection and model average estimators in parametric models. Despite the burgeoning literature on Tobit models, little work has been done on model selection explicitly in the Tobit context. In this article we propose FICs for variable selection allowing for such measures as mean absolute deviation, mean squared error, and expected expected linear exponential errors in a type I Tobit model with an unknown threshold. We also develop a model average Tobit estimator using values of a smoothed version of the FIC as weights. We study the finite-sample performance of model selection and model average estimators resulting from various FICs via a Monte Carlo experiment, and demonstrate the possibility of using a model screening procedure before combining the models. Finally, we present an example from a well-known study on married women's working hours to illustrate the estimation methods discussed. This article has supplementary material online.

The Determinants of YIC's R&D Activity

This paper examines the determinants of young innovative companies’ (YICs) R&D activities taking into account the autoregressive nature of innovation. Using a large longitudinal dataset comprising Spanish manufacturing firms over the period 1990-2008, we find that previous R&D experience is a fundamental determinant for mature and young firms, albeit to a smaller extent in the case of the YICs, suggesting that their innovation behavior is less persistent and more erratic. Moreover, our results suggest that firm and market characteristics play a distinct role in boosting the innovation activity of firms of different age. In particular, while market concentration and the degree of product diversification are found to be important in boosting R&D activities in the sub-sample of mature firms only, YICs’ spending on R&D appears to be more sensitive to demand-pull variables, suggesting the presence of credit constraints. These results have been obtained using a recently proposed dynamic type-2 tobit estimator, which accounts for individual effects and efficiently handles the initial conditions problem.

Aid for AIDS in Africa

This article applies a two-tiered contribution model to ascertain the determinants of donors’ participation and contribution levels to giving aid for controlling HIV/AIDS in Africa. Bayesian spatial estimates for the two-tiered model are presented for 22 donor countries that gave aid to 48 recipient countries during 2000–2007. We account for the public nature of HIV/AIDS contributions by including the contributions of other donors as a determinant at both participation and expenditure stages, along with standard determinants of general assistance. Independent variables account for altruistic, political, economic, location, institutional, and environmental factors. Donor’s reaction to spillovers differs in the two stages, thereby supporting the two-tiered estimates over the single-stage Tobit estimates. Aid for AIDS in Africa is motivated by a complex mix of strategic (publicness), altruistic, and donor self-interests. Key factors at both stages include donors’ spillovers, rule of law, past colonial ties, sharing a common language, trade, and people living with HIV. A host of robustness tests are presented.

Tobin as an Econometrician

Best known as a Keynesian macroeconomist and monetary theorist, James Tobin was also actively engaged in empirical economics from his doctoral dissertation onward. His innovative combination of time-series data with household budget surveys in his 1947 dissertation and 1950 food demand study, and his 1955 and 1958 papers on limited dependent variables (Tobit estimation), were contributions to econometrics, not just the use of existing techniques by an applied economist. The present essay examines Tobin's involvement with econometrics from his student days “teaching myself econometrics” at Harvard to his later advocacy of an approach to empirical macroeconomic modeling based on his “general equilibrium approach to monetary theory” that contrasted sharply with new classical macroeconomic modeling that interpreted general equilibrium in a very different way.

Discouraging Workers: Estimating the Impacts of Macroeconomic Shocks on the Search Intensity of the Unemployed

Discouraged and marginally attached workers have received increased attention from policy makers over the past several years. Theoretically, periods of recessions and high unemployment should directly influence individual’s decisions whether or not to search for employment, creating more discouraged workers. Since 2003, there have been a number of large macroeconomic shocks (e.g. housing bubble, credit crunch, mass layoffs, etc.) which should affect job search intensity. To date, the relative magnitude of these shocks on the search intensity of the unemployed (but currently undiscouraged workers) has not been established in the literature. Using daily time use dairies from the American Time Use Survey 2003-2009 allow us to proxy search intensity directly by aggregating time spent in minutes on several job search activities: time spent sending out resumes, contacting employers, interviewing, reading ads on the internet and so forth. Results from Tobit estimation indicate the existence of significant negative wealth effects on search intensity through changes in the stock market and housing values that help explain the apparent acyclicality of search intensity observed in the data.

Farm Size, Modern Technology Adoption, and Efficiency of Small Holdings in Developing Countries: Evidence from Kenya

Low efficiency is a problem in most developing agriculture, and is one of the reasons for food insecurity. This paper provides information on smallholder production efficiency in one of the developing Sub-Saharan Countries: Kenya. It applies Data Envelopment Analysis (DEA) to farm-level seasonal panel data. The estimated indexes indicate high levels of inefficiency between farm sizes, seasons, and adopters and non-adopters of 'modern' farming technologies. A comparison of various farming practices shows that use of modern inputs and livestock-based capital could significantly improve farmers' performance. Tobit estimations show that the major factors influencing performance are the level of education, gender, market access and off-farm capital. Thus, policies aimed at improving education, rural infrastructure as well as assuring farmers of income through improved livelihood opportunities, and therefore reduced perceived uncertainty, could improve farm-level efficiency. The findings also provide support for prioritizing issues of farm production associated with women in policymaking.

Assessing the implications of regional preferential market access for meat commodities

The authors derive a gravity framework that is compatible with the existence of reference prices for agricultural commodities. A commodity-specific gravity equation, estimated with Poisson pseudo-maximum likelihood and threshold Tobit estimators, is used to investigate the effects of regional trade preferences for meat commodities. The predictions indicate that European Union (EU) tariff-free access and North American Free Trade Agreement (NAFTA) nontariff provisions are the main types of preferences that substantially promoted intraregional trade. In addition, the trade creation effects of the Mercado Comun del Sur (MERCOSUR) and Andean Community of Nations (ANDEAN) are generally the result of nontariff preferences. Moderate trade diversion effects occurred in the case of the EU, NAFTA, and MERCOSUR. [Econ Lit classification: F14, F15, Q17]. © 2011 Wiley Periodicals, Inc.

Determinants of Migrants’ Earnings and Remittances: Evidence from Kosovo

This paper is an attempt to find the main determinants of migrants’ earnings and analyze what makes migrants remit money to their home countries. We use the dataset on migrants compiled by the Riinvest Institute in 2006. Ordinary least squares (OLS) and interval regression methods are used to estimate the migrants’ earnings model, while for the remittances model we use OLS and Tobit estimation methods. The results suggest, inter alia, that the returns to education are positive for migrants; also, migrants in countries with higher per capita GDP have higher family earnings. Among the most important determinants of remittances are migrants’ investments in their home countries, migrants’ perceptions of the business environment, migrants’ earnings, gender and the duration of migration. This paper tries to fill the gap in the literature, especially for the case of Kosovo, by exploring what determines the earnings of migrants and what makes migrants remit part of these earnings.

The Income Elasticity of Lottery: New Evidence from Micro Data

The authors analyze consumer expenditure on the National Lottery in Spain, a popular game with over 100 draws per year and annual turnover of about three billion euros. Based on Tobit estimates using data from two nationally representative surveys, National Lottery players tend to be middle-aged married males with relatively low education. In contrast to previous research, the authors find a strong relationship between lottery expenditure and income, with estimated income elasticities of more than one. A parameter decomposition indicates that the effect of income on expenditure works through existing lottery players, not by attracting new players.

Education Funding in Massachusetts: The Effects of Aid Modifications on Vertical and Horizontal Equity

Public school funding in Massachusetts is based on foundation budget principles. However, funding formula modifications often create disparities between district foundation budgets and actual required spending levels. This study provides an in-depth look at Massachusetts' state aid formulas used between 2004 and 2009 and utilizes two approaches to measure the effects of aid modifications on vertical and horizontal equity. The first is a regression-based approach which compares the intended effects of student characteristics on foundation spending to the actual effects on required spending. The second approach measures equity directly for each school district and uses the Tobit estimation technique to examine the effects of student and district characteristics on the equity measure. Results indicate that district characteristics such as community wealth and regional school systems increase the likelihood of a district benefiting from aid modifications. Holding community characteristics constant, there is also evidence that districts with high proportions of low income elementary school students and/or English language learners benefit from overlay provisions as well.

R&D Drivers in Young Innovative Companies

This paper examines the determinants of young innovative companies' (YICs) R&D activities taking into account the autoregressive nature of innovation. Using a large longitudinal dataset comprising Spanish manufacturing firms over the period 1990-2008, we find that previous R&D experience is a fundamental determinant for mature and young firms, albeit to a smaller extent in the case of the YICs, suggesting that their innovation behaviour is less persistent and more erratic. Moreover, our results suggest that firm and market characteristics play a distinct role in boosting the innovation activity of firms of different age. In particular, while market concentration and the degree of product diversification are found to be important in fostering R&D activities in the sub-sample of mature firms only, YICs' spending on R&D appears to be more sensitive to demand-pull variables, suggesting the presence of credit constraints. These results have been obtained using a recently proposed dynamic type-2 tobit estimator, which accounts for individual effects and efficiently handles the initial conditions problem.

Gravity Approach for Modelling International Trade in South-Eastern Europe and the Commonwealth of Independent States: The Role of Geography, Policy and Institutions

Since the beginning of market reforms in 1989, countries of the South-Eastern Europe (SEE) and the Commonwealth of Independent States (CIS) trade significantly less with the world economy than those Central and Eastern European (CEE) countries which later joined the EU. To explain why this is the case, a number of hypotheses have been proposed in the literature. The key novelty of our study consists in a simultaneous assessment of the contribution to trade from geographical, policy and institutional factors, during the EU pre-accession period (1997–2004). An augmented gravity model is proposed and estimated for a reference group of 82 countries employing the Poisson and Tobit estimation techniques. We find that the low quality of economic institutions in the SEE and CIS countries contributed to a considerable proportion of their below potential international trade. We perform policy simulations using institutional data up to 2008 to identify channels for increasing international trade of the SEE and CIS.

Effects of harvesting of the namibian kelp (<i>Laminaria pallida</i>) on the re-growth rate and recruitment

Using data from a survey of loan applicants and bank officials from Union Bank of Nigeria and First Bank of Nigeria in south-western Nigeria, this paper empirically evaluated the determinants of loan approval decision and the size of the loan given using a Tobit regression model. With a multi-stage sampling technique, data were collected with the aid of structured questionnaire drawn on 450 applicants. The respondents’ ages varied between twenty five years and sixty nine years with a mean of fifty and a half years for all the respondents. The mean age recorded for each category of respondents suggests that middle-aged farmers who are expected to be economically active and energetic dominated the sampled population. They should be willing to explore avenues and adopt new methods in order to raise their level of productivity. The relatively large farm sizes owned by the applicants indicated that it is one of the major criteria for giving loans to the farmers; hence those with very small farm sizes may not have access to loans from the two institutions. Tobit estimates show that institutional, environmental and part of the resource variables were important determinant factors of loan approval decision and a decomposition of elasticities calculated at the mean of the variables revealed that a 10% increase in the RISK variable will lead to a total elasticity change of about -0.79 %. This indicates that the elasticity of probability of loan approval will decrease by about 0.36 % and elasticity of expected loan size will decrease by 0.43%. The result tends to imply riskaverseness of the lenders, as fewer loans are granted. The positive coefficient of HHZE indicated that high farm assistance was received from respondents’ relations who positively influenced the implications for family labour and cultivation of large area of land and eventually influenced the approval decision. The coefficient of NFI positively influenced the loan approval decision since the farmer can expand his options to acquire more loans and use for profitable ventures since this variable is viewed as a proxy for wealth, thus the beneficiary will have sufficient resources to absorb the cost and risk of failure in their agricultural enterprises. In each of the two institutions, the marginal changes in most of the variables considered increased the probability of loan size influence than it increased the probability of approval. Key words: Lending Decision, Tobit Regression, Credit

Agricultural lending decision: a tobit regression analysis

Using data from a survey of loan applicants and bank officials from Union Bank of Nigeria and First Bank of Nigeria in south-western Nigeria, this paper empirically evaluated the determinants of loan approval decision and the size of the loan given using a Tobit regression model. With a multi-stage sampling technique, data were collected with the aid of structured questionnaire drawn on 450 applicants. The respondents’ ages varied between twenty five years and sixty nine years with a mean of fifty and a half years for all the respondents. The mean age recorded for each category of respondents suggests that middle-aged farmers who are expected to be economically active and energetic dominated the sampled population. They should be willing to explore avenues and adopt new methods in order to raise their level of productivity. The relatively large farm sizes owned by the applicants indicated that it is one of the major criteria for giving loans to the farmers; hence those with very small farm sizes may not have access to loans from the two institutions. Tobit estimates show that institutional, environmental and part of the resource variables were important determinant factors of loan approval decision and a decomposition of elasticities calculated at the mean of the variables revealed that a 10% increase in the RISK variable will lead to a total elasticity change of about -0.79 %. This indicates that the elasticity of probability of loan approval will decrease by about 0.36 % and elasticity of expected loan size will decrease by 0.43%. The result tends to imply riskaverseness of the lenders, as fewer loans are granted. The positive coefficient of HHZE indicated that high farm assistance was received from respondents’ relations who positively influenced the implications for family labour and cultivation of large area of land and eventually influenced the approval decision. The coefficient of NFI positively influenced the loan approval decision since the farmer can expand his options to acquire more loans and use for profitable ventures since this variable is viewed as a proxy for wealth, thus the beneficiary will have sufficient resources to absorb the cost and risk of failure in their agricultural enterprises. In each of the two institutions, the marginal changes in most of the variables considered increased the probability of loan size influence than it increased the probability of approval.Key words: Lending Decision, Tobit Regression, Credit