Search results

Research on strategic choices available to the firm are often modeled as a limited number of possible decision outcomes and leads to a discrete limited dependent variable. A limited dependent variable can also arise when values of a continuous dependent variable are partially or wholly unobserved. This chapter discusses the methodological issues associated with such phenomena and the appropriate statistical methods developed to allow for consistent and efficient estimation of models that involve a limited dependent variable. The chapter also provides a road map for selecting the appropriate statistical technique and it offers guidelines for consistent interpretation and reporting of the statistical results.

The purpose of this study is to examine tax stamp evasion at Twifu Atti-Morkwa and Hemang Lower Denkyira districts in the central region of Ghana.

A cross-sectional survey design was adopted to sample 305 micro-taxpayers through the use of multi-stage sampling technique. Primary data were collected from the micro-taxpayers using structured interview. Binary and multinomial logit regression models were used to regress the tax stamp evasion on economic and non-economic factors.

The study found that the likelihood of micro taxpayers to evade tax stamp is predicted by age, application of sanctions, guilt feeling, transportation cost to tax office and rate of tax audit. Thus, the study found partial support for expected utility, planned behaviour and attributory theories in explaining tax evasion behaviour of micro-taxpayers.

There are several measures of addressing tax evasion behaviour of micro taxpayers. Evasion behaviour can be deterred by enforcement strategies such as application of sanctions and regular tax audit, establishment of more tax offices in the districts and writing normative messages on the faces of tax stamp stickers.

This study helps explains the tax evasion behaviour of micro-taxpayers of a developing economy like Ghana using a special type of tax design meant to capture such taxpayers in the tax bracket. To the best of our knowledge, the study is unique in terms of the means of measuring tax evasion and the methodologies used.

Improved indigenous chicken is considered a sustainable agricultural practice with social, economic and environmental indicators. Therefore, the analysis of the choice of market channels is of considerable importance to farmers with reference to improved livelihoods and poverty alleviation in developing countries. The purpose of this study is to investigate the factors that influence market channel choices among improved indigenous chicken farmers in Baringo County and to rank the determinants according to their level of importance in influencing farmer's choice of marketing channels.

A multistage sampling technique was employed to collect data from 209 households for the study conducted between April and July 2019, out of which, 198 useful responses were obtained. Multinomial logit regression and neural network models were used to analyze the factors influencing market channel choice based on socioeconomic, demographic and farm characteristics.

It was established that group membership, education, market distance, transport costs, farm size, cost of information and bargain costs were statistically significant in the choice of market channels (wholesaler, brokers, processors and supermarkets). With the direct consumer as the base market choice. The cost of transport had the highest normalized importance in the prediction of a farmer's selection of market channels for both radial basis function (RBF) and multilayer perceptron (MLP) neural networks. However, flock attributes and age of household head had the least normalized importance in MLP and RBF, respectively.

Due to the insufficiency of resources and time, this study only focused on a small part of the country (Baringo County). However, improved indigenous chicken farming is widely practiced in Kenya. Further studies can be carried out in other counties to validate the results of this study.

The outcome can be used in policy implementation involving improved indigenous chicken production in Kenya.

This study suggests the methods aimed at enhancing poultry sector in other counties in Kenya as well as other developing countries.

This paper aims at investigating the link between inter-organizational relationships and innovation, discussing whether the probability to detect a greater innovation propensity of organizations increases with or without collaborative partnerships.

Drawing on secondary data provided by the Italian Institute of Statistics (ISTAT) about a representative sample of 8,967 Italian firms, three multinomial logit models and four logit models have been estimated, in an attempt to examine the effects of inter-organizational relationships on different types of organizational innovation.

A positive and statistically significant relationship between inter-organizational relationships and organizational innovation emerged from all the models which were arranged for the purpose of this study. Several categories of partners, including suppliers, universities and firms belonging to the same holding group, were found to be more effective in fostering the probability of organizational innovation. Interestingly, geographical proximity did not seem to influence the organizational propensity to innovate.

Even though further developments are needed to disentangle the complex link between inter-organizational relationships and organizational innovation, the former are likely to positively affect the innovation ability of organizations. From this point of view, it could be argued that partners perform as catalysts, which boost the knowledge creation process underlying the emergence of organizational innovation.

This is one of the first attempts to exploit the potential of multinomial logit models and logit models to investigate the effects of inter-organizational relationships on the propensity of organizations to innovate.

The purpose of this paper is to examine the factors associated with three modes of firms’ exit (voluntary liquidation, involuntary liquidation and acquisition) in a mutually exclusive environment. In particular, three modes of exit are treated as independent events given that different causes and consequences exist for each exit mode. The data set is a panel of 4,408 US manufacturing firms spanning over the period 1976–1995.

The discrete choice model is used to establish a relationship between modes of exit and a set of explanatory variables, which are specific to the firm, industry and macroeconomic conditions. Use of panel data encourages us to estimate a random effects multinomial logistic regression model, which allows exit modes as mutually exclusive events and at the same time controls the firm-specific unobserved heterogeneity in the sample.

The analysis suggests that the determinants of voluntary liquidation are age, size, profitability, technology intensity and inflation level. The determinants of involuntary liquidation are size, leverage, profitability and inflation level. For acquisition, determinants are age, size, advertising intensity, Tobin’s q, GDP growth, inflation level and interest rate. The findings suggest that exit modes have a different set of determinants and the scale of effects of some common determinants such as age, size and profitability differs between exit modes.

The analysis presented in this study relies on data from US manufacturing firms only. Thus, there is a need to explore the determinants of exit modes in other countries as well using the proposed econometric model.

The findings presented in this paper are useful for managers and policymakers to design strategies/actions for avoiding particular mode of exit.

This study provides empirical evidence on the differences in factors associated with exit modes and confirms the existence of mutually exclusive nature of exit modes. Findings suggest that for future empirical studies on firm exit, the exit modes must be treated as a heterogeneous event.

To investigate the extent to which disability discourages an individual from going on the job market, using data from an Italian survey.

We use an extended definition of labour force participation based on being employed or currently seeking work even if the persons declare themselves as housewives, students, retired or in any other condition otherwise. We use probit, sequential and multinomial logit models for analysing labour force participation and outcomes. We distinguish between the impact of disability in its strict sense and chronic illness explaining the difference.

In all variants we find that chronic illness is a stronger deterrent for labour force participation than disability. Women are more discouraged compared to men. Intellectual disability is the strongest barrier and hearing the least influential. In a sequential decision-making process, we find that disability affects both labour force participation decision and the ability to be employed but not so much the choice between part-time and full-time.

Policies providing tailored solutions for improved access to education and health care for disabled persons will enhance their work opportunities.

Data set is cross-sectional and characterised by attrition. It would be interesting to compare results with a longitudinal and more representative data set.

We have a unique data set from a survey which was specifically targeted at people who were identified as disabled in a previous survey. The Italian context is also special due to its high legal employment quotas and noncompliance sanctions.

Evaluating a portfolio of agricultural loans has become an important issue in recent years primarily due to a large number of loan defaults. The purpose of this paper is to investigate the factors influencing credit repayment behavior of farmers in Karnataka.

The study is based on secondary data of 590 farmers collected from a private bank in the state of Karnataka, India. Binary logistic regression and multinomial regression analysis was carried out to estimate the probability of non-payment of a loan.

The results of the regression confirm a significant relationship between non-repayment of agricultural credit and characteristics of borrowers such as the age, years of banking relationship, yield of the crop, distance to bank branch, size and tenure of the loan, farm size and leverage and efficiency ratio.

The factors predicted by the model do certainly help in improving the decision-making process in agricultural lending. A rigorous assessment of family responsibilities, farm size, credit-to-asset ratio, interest burden on the farmers and farm income is suggested to reduce the probability of doubtful assets.

The studies that predict default risk in agricultural loan are limited in India. This is one of the few studies that estimate the determinants of substandard and doubtful categories of credit in a private sector bank.

The purpose of this paper is to examine female labour force participation (FLFP) and their employment choice between the formal and informal sectors after several institutional and social reforms such as Millennium Development Goal 3 aimed at promoting gender equality and empowerment of women by 2015, using data from Ghana’s 2010 Population and Housing Census.

In this paper, logit regression and multinomial logit techniques were employed.

The results show that FLFP has declined marginally from the 2005 figures; education remains the important factor in determining women’s participation in the formal sector. Strikingly 91 per cent of the FLFP is engaged in the informal sector of the Ghanaian economy, a sector with a very low contribution per head.

Interventions such as encouraging female education and retraining of self-employed females to improve upon their efficiency ought to be pursued vigorously; whiles developing rural areas for females to get equal labour opportunities and many others aimed at enhancing the efficiency and by inference earning per head of the informal sector is highly recommended.

The literature on the FLFP is thin in Ghana. The current study uses a census data unlike the previous studies and as such employed a huge sample size that reflects the reality in Ghana. The study contributed immensely to policy having established that 91 per cent of the female labour force is engaged in the informal sectors of the economy, and therefore any intervention targeting at reducing poverty and meeting the MDG 3 should be targeted at the informal sector of the Ghanaian economy.

The labourforce status of members of American Mensa (a high IQ group) is examined. Compared with a general US sample, the Mensans′ labour‐force participation rate was found to be higher, while the percentage not in the labourforce was lower. Multinomial logit estimation indicates that demographic variables have greater influence on the odds of individuals being in the various labourforce categories for the general US sample than for Mensans. Differences in labourforce patterns for Mensans versus the US sample are due more to differences in characteristics than to underlying behavioural differences.