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We assess if capital ratios reduced the occurrence of banking crises in the European Union from 1998 to 2017. We use a Probit model and estimate the effect of two measures: the bank capital to total assets ratio and the bank regulatory capital to Risk Weighted Assets (RWA). We found that both measures affect negatively the probability of crisis. This result is robust to the exclusion of outliers, to the inclusion of various control variables for banking, financial and macroeconomic risks. Finally, we show that while the bank regulatory capital to RWA has always a negative effect on the probability of crisis, the bank capital to total assets ratio is only significant above a threshold, estimated between 10 ​% and 12 ​%.

Recent empirical evidence has shown that firm’s innovation behavior exhibits high persistency but not much is known about potential contingencies affecting the degree of persistence. This paper focuses on the role of the local knowledge environment and asks how local knowledge spillovers affect firms' innovation persistence. The empirical analysis draws upon a representative panel data set of firms in Germany from 2002-2016, complemented by detailed geographic information of patent activity over discrete distances to proxy local knowledge spillovers. Based on correlated random effects probit models that control for state dependence, unobserved individual heterogeneity and endogenous initial conditions, our results corroborate former evidence that persistency in innovation is driven by true state dependence. More importantly, we find that the local patenting activity positively moderates firms' degree of persistency in innovation behavior. This is a novel firm-level mechanism that can explain the widening of spatial disparities in innovation performance. Estimations with different distance bands show that the strength of knowledge spillovers that contribute to innovation persistence via true state dependence declines rather rapidly with increasing distance.

Agricultural policymakers call for the operationalisation of farm resilience as a dynamic concept. Therefore, we quantify farm resilience along the dimensions of robustness, adaptation and transformation. Using the rich Farm Accountancy Data Network panel data set, we explore which farm(er) characteristics affect resilience. We employ a control function approach to address the presence of endogeneity in correlated random effects (fractional) probit models. In general, we find that decoupled payments negatively affect robustness, while rural development payments have a positive effect on robustness. Both decoupled and rural development payments have no effect on adaptation and transformation in most European regions.

This paper seeks to examine the unidirectional versus bidirectional Granger causality between investors’ sentiment and momentum strategies. It is based on the full sample Granger causality test and the recent rolling-window bootstrap approach. We also applied a probit model to the extent to which the probability that investors’ sentiment and momentum strategies influence each other. Our results suggest bidirectional Granger causality between investor sentiment and momentum strategy with unstable causality dynamics over time. We find that ADS and VIX positively affect the likelihood that investor sentiment Granger causes momentum strategy and negatively impact the probability that momentum strategy Granger causes investor sentiment. Gold harms the likelihood that investors’ sentiment and momentum strategies affect each other. The research design is unique to combine bootstrap rolling-window Granger causality tests between Sentiment and Momentum to assess investors’ implications in terms of confidence, uncertainty, aggressiveness, or optimism versus Pessimism.

This paper examines the role of peer effects on farmers’ decision to adopt Unmanned Aerial Vehicles (UAVs). This relationship is analysed by means of a Bayesian spatial autoregressive probit model ...

Temporary employment is widely used in European countries for new hires to avoid strict employment protection legislation against dismissal of permanent workers. In this respect, temporary employment works as an extended probation period enabling employers to monitor the productivity of new entrants. However, the use of temporary contracts is quite limited in Turkey due to legal restrictions. We argue that the restrictions on temporary employment together with rigid job security provisions for permanent employees lead to a rise in informality among young. To test this hypothesis, we use the variation between industries in terms of the gap between the desired and actual share of temporary workers among young. Since desired share is not observed, we proxy it with the share in Germany, where legislation on temporary employment is loose and informality is negligible. We estimate a probit model using individual level data from the Household Labor Force Survey for the period 2009–2018. We find that restrictions on temporary employment increase informality among male and under-educated workers in Turkey. Our results are robust to using other countries with loose regulations on temporary employment. We should note that our results do not imply that informality merely comes from restrictions on temporary employment.

Despite the risk associated with nuclear energy, it represents an attractive climate change mitigation option and energy supply security. We examined how South African households perceive nuclear energy in the context of climate change mitigation, risk and avoidance of power outages. The objective of this study is to investigate households’ willingness to pay (WTP) for the proposed second nuclear power. Traditional analysis of such data has tended to ignore zero WTP values. A spike model (i.e., ‘two-part model’) which explicitly accounts for zero WTP is employed. We also test for effect of distance on WTP. The Thyspunt dummy is negative and significant in the probit model, which implies that those who are closer to the plant are more likely to state a zero WTP. The second decision, WTP given positive WTP, modelled with a truncated regression model suggests that putting more distance between residences and the nuclear plant would have little effect on WTP. Therefore, distance is not a relevant predictor of WTP for solving the problem of nuclear-related risk. Higher dependence on electricity is most likely to lead people to be more supportive of the planned plant.Keywords: climate change, distance, electricity, nuclear, willingness to pay.JEL Classifications: Q42, Q48, Q51, Q54DOI: https://doi.org/10.32479/ijeep.11343

Background Out-of-pocket (OOP) health expenditure is a pressing issue in Egypt and far exceeds half of Egypt’s total health spending, threatening the economic viability, and long-term sustainability of Egyptian households. Targeting households at risk of catastrophic health payments based on their characteristics is an obvious pathway to mitigate the impoverishing impacts of OOP health payments on livelihoods. This study was conducted to identify the risk factors of incurring catastrophic health payments hoping to formulate appropriate policies to protect households against financial catastrophes. Methods Using data derived from the Egyptian Household Income, Expenditure, and Consumption Survey (HIECS), a multiplicative heteroskedastic probit model is applied to account for heteroskedasticity and avoid biased and inconsistent estimates. Results Accounting for heteroskedasticity induces notable differences in marginal effects and demonstrates that the impact of some core variables is underestimated and insignificant and in the opposite direction in the homoscedastic probit model. Moreover, our results demonstrate the principal factors besides health status and socioeconomic characteristics responsible for incurring catastrophic health expenditure, such as the use of health services provided by the private sector, which has a dramatic effect on encountering catastrophic health payments. Conclusions The marked differences between estimates of probit and heteroskedastic probit models emphasize the importance of investigating homoscedasticity assumption to avoid policies based on incorrect evidence. Many policies can be built upon our findings, such as enhancing the role of social health insurances in rural areas, expanding health coverage for poor households and chronically ill household heads, and providing adequate financial coverage for households with a high proportion of elderly, sick members, and females. Also, there is an urgent need to limit OOP health payments absorbed by private sector to achieve an acceptable level of fair financing.

This paper assesses the convergence of the EU-28 countries toward their common goal of 20% in the renewable energy share indicator by year 2020. The potential presence of clubs of convergence toward different steady-state equilibria is also analyzed from both the standpoints of global convergence to the 20% goal and specific convergence to the various targets assigned to Member States. Two clubs of convergence are detected in the former case, each corresponding to different renewable energy source targets. A probit model is also fitted with the aim of better understanding the determinants of club membership, which seemingly include real GDP per capita, expenditure on environmental protection, energy dependence, and nuclear capacity, with all of them having statistically significant effects. Finally, convergence is also analyzed separately for the transport, heating and cooling, and electricity sectors.

In recent times, household loans, which is a tool for development for most households have gained much importance especially in developing countries. This can be attributed to the fact that they are likely to have a significant impact on the welfare of the households. This study provides evidence on the impact of household loans on the welfare of households in Ghana. The study also examines the factors that influence the probability that households will have access to loans. Data for the empirical analysis are obtained from the sixth round of the Ghana Living Standards Survey (GLSS6). The study employs the Heckman probit, a probit model with sample selection, to determine the factors that influence the probability that households will be granted loans. The analysis reveals that 90.6% of the total household heads who applied for loans were granted and determinants such as marital status (previously in a union) and educational level (tertiary level) of the household head influence the probability that loans will be granted to households. The propensity score matching (PSM) technique is used to analyse the impact of household loans on household welfare. The analysis shows that household loans have a positive and significant impact on household welfare.

Child mobility is a significant phenomenon all over the world and is especially prominent in developing countries, where it is made worse by income conditions in rural households. The aim of this p...

The aim of the article is to answer the question whether the tax benefits that can be obtained by the self-employed in Poland influence the decision to start their own business. In the study, the EUROMOD microsimulation model is used to determine tax benefits from self-employment. The estimated tax benefits are then used in a probit regression to explain the probability of self-employment. The survey is carried out for both original EU-SILC data and adjusted data, assuming that the income reported by the self-employed is underreported. The results of the survey based on the original data indicate that taxpayers make irrational decisions about taking up self-employment. This is because as the benefits of self-employment increase, the probability of self-employment decreases. After ad-justing the data on self-employed income with the underreported income, the results of the analysis lead to the opposite conclusion.

The current study examines sources of bargaining power that inform financial decision‐making processes within co‐resident couples and determines how bargaining power and decision‐making impact on family‐type public goods expenditure. The study uses South Africa's National Income Dynamics Study, which offers a direct measure of financial decision‐making responsibility. In terms of analysis, probit regression models are used to establish socioeconomic determinants of decision‐making for female partners in co‐resident couples, while ordinary least squares linear regression models are employed to determine the extent to which financial decision‐making responsibility and power influence expenditure on family‐type public goods by households. There is evidence of the relevance of economic factors in explaining financial decision‐making as postulated by the resource theory. Households with wives who gain a decision‐making role spend more on family‐type public goods. The findings suggest that policy has to focus on gender mainstreaming and empowerment, which would enhance the decision‐making role of women within co‐resident couples.

Brain drain is one of the important aspects of development economics/Demographic transitions. A populous country has the potential to export human capital. There are so many determinants of Human Capital Outflow (HCO). Some like economic, social, and political drivers are already discussed in the previous studies. This study compares the impact of various classes of variables on the HCO. Furthermore, it gives recommendations for controlling HCO based on such results. Data is collected in the form of questionnaires from three rural and three urban areas of Peshawar. Random sampling is used. Probit models are used for comparing the significance of variables. The study shows that not only the classic variables, i.e. economic, social and political are important but also the newly introduced religious and environmental factors have a great impact on HCO. The forthcoming researchers can do further study by considering even more factors affecting the HCO. They can conduct studies for different areas and on different scales.

The health crisis caused by the COVID-19 pandemic will have repercussions in all spheres of society. The pandemic’s potential effects on remittances were discouraging at the beginning of the crisis, yet the amounts of international remittances received in Mexico during the pandemic did not show the expected forecast. In an attempt to respond to the apparently unexpected trends in remittances, this article aims to discover an explanation in the theoretical foundations in the literature with respect to migrants’ motivation in sending remittances. Using a probit model and data from Mexico’s National Survey of Household Income and Expenditures (Encuesta Nacional de Ingresos y Gastos de los Hogares--ENIGH) from 2016 and 2018, the findings suggest that altruism is the primary motivation behind the behavior of remittances in the scenarios of the health crisis in the migrants’ households of origin.

This study analyses the persistence and true state dependence of overqualification, i.e. a mismatch between workers' qualifications and their jobs' educational requirements. Employing individual-level panel data for Germany, I find that overqualification is highly persistent among tertiary graduates over the first ten years of their career cycle. Accounting for unobserved heterogeneity, results from dynamic random-effects probit models suggest that only a small share of the observed persistence can be attributed to a true state dependence effect. Unobserved factors are found to be the main driver of the high persistence of overqualification. In particular, selection into initial overqualification at the start of the career is of high importance. Furthermore, overqualification persistence is shown to be partly attributable to observed heterogeneity in terms of ability and study characteristics.

In this article, we study a panel data probit model with time-varying individual effects. Under a Gaussian assumption on the error term, we show the common slope coefficients and time factors can be identified up to scale. We propose for the identified parameters a multi-stage estimation procedure. The proposed estimators have a closed form expression, thus are very convenient to compute even in large samples. We establish the root-n consistency as well as asymptotically normality for these estimators. Using a German socioeconomic panel dataset, we estimate the labor supply function for married women. We find that the unobserved skill premium is positive and shows an upward trend during 2008–2012, in support of the biased technological progress hypothesis.

This study examines the influence of household real estate on self-employment probability using a probit model based on four-phase Chinese General Social Survey microsurvey data. Our baseline results show that household real estate substantially increases the probability of personal self-employment. To solve endogeneity, we consider the Chinese marriage tradition in which parents who have male offspring prepare more real estate for their children. Using child gender ratio as an instrumental variable of household real estate, we find that real estate has a significant positive effect on self-employment. Moreover, real estate enhances a family’s risk-sharing ability, thus increasing the probability of individual self-employment. Household real estate helps enhance an individual’s social capital, thereby promoting self-employment. However, household real estate also promotes other personal investment, such as stocks, funds, and other assets, forming a crowd-out effect on self-employment.

This study examined the determinants of rural household agriculture credit fungibility (CF). The study found agricultural CF among farmers, with approximately 79% of farmers involved in agricultural CF. Household financial burden was found to be the main cause of CF among the studied farmers. Most fungible credit was used for clothing and food consumption. A probit model was employed to analyze survey data collected from four regions in Ghana. We employed an instrumental variable approach (IV-Probit) to test for robustness due to endogeneity issues. The econometric model results show that the variables of off-farm income and farm size inversely influenced agricultural CF, while those of education, household size, male farmer gender, and chronic disease variables had a positive effect on agricultural CF. Our findings have policy implications for alleviating agricultural CF.

Small and medium-sized enterprises (SMEs) have a vital position in the international economy. The study aims to examine the compulsory financial reporting requirements set by the Kosovo Council for Financial Reporting (KCFR) as well as SMEs requirements for reviewing the current classification in the Kosovo context. This study, like most relevant studies, employs ordinal probit regression to examine the relationships among the requirements defined as dependent variables and other control variables such as necessary reclassification review under KCFR, preferred reclassification review under KCFR, experience knowledge of accountants and auditors, continuously education concerning financial reporting, and assessments of business owners. According to the reported conclusions, the application of these requirements in the Kosovo context does not create any opportunities for SMEs. On the contrary, the findings point to a thorough review of the reporting requirements for micro-businesses, as the current classification appears to be a burden for these businesses.

In this paper, we investigate the macroeconomic, demographic and institutional factors affecting the probability of growth slowdown in upper-middle-income countries within the framework of the growth slowdown methodology developed by Eichengreen et al. (2011). To do so, we use probit regression, and the dataset covers the period 1980-2015. The results show that growth slowdown occurs when per capita income reaches 22 percent of that in the United States. Besides, an increase in the relative income, gross capital formation, trade openness, years of total schooling, old dependency ratio and law and order index increases the risk of growth slowdown, whereas an increase in public debt, inflation variability and years of secondary and higher schooling decreases the risk of growth slowdown.

This study applies spatial econometric techniques to evaluate the effect of external economic agents located in agri‐food business environments on the probability of those businesses failing. A logistic regression model that incorporates spatial interactions has been applied to the data. In addition, the article proposes an intermediate step in the modeling process based on generalized additive models to determine the specific functional relationships between the probit model and the explanatory variables. The results reveal that geographic location has a significant effect on the probability that agri‐food companies fail to find significant nonlinearities. [EconLit Citations: G33, Q14, R10]

This paper investigated the determinants of the gender gap in financial inclusion in Namibia, a country where women are more financially included than men. We employed the probit model to identify the determinants of financial inclusion and the Fairlie decomposition to examine the contribution of these factors to the gender gap in financial inclusion. The results suggest that the observed gender gap in financially included is insignificant. We found that individual characteristics such as financial literacy, educational attainment and proximity to financial institutions, contribute positively and significantly to the observed gender gap. Thus, any policy action geared towards improving the level of financial inclusion of disadvantaged women should focus on enhancing their level of education, financial knowledge and access (proximity) to financial institutions. However, the contribution of other individual and household characteristics cannot be completely ignored.

By employing Alkire and Foster (J Public Econ 95(7–8):476–487, 2011a) counting approach and Cerioli and Zani (A fuzzy approach to the measurement of poverty, Springer, Berlin, 1990) unequal weighting method, this study estimates the non-monetary multidimensional poverty in Ethiopia for three waves with fourteen country-specific indicators and four dimensions in its first part; and tried to identify the presence of state dependence with unobserved heterogeneity using dynamic random effect probit model with unobserved heterogeneity estimation technique in its second part. The data for the three waves are from Demographic and Health Survey (DHS) of Ethiopia for the year 2005, 2011 and 2016. The panel estimation of non-monetary multidimensional poverty gives a higher level of multidimensional poverty compared to the reports from international organizations, mainly from OPHI and UNDP, in respective years. This is mainly due to the additional indicators and the weighting method used. Housing, cooking fuel, toilet and sanitation and electricity played a significant role compared with the other indicators for the high non-monetary multidimensional poverty in the country. It is also found that there is a substantial and positive impact of the previous poverty status of households for their future experience in poverty. Households living in rural areas are more prone to experience poverty and have low chance to exit from poverty compared to urban households. In addition to focus on infrastructure development in fighting poverty, the governments’ development policies and strategies should target households who are experiencing poverty trap mainly those who are living in rural areas.

In this study, we use data from an online lending platform named Xinxindai in China to empirically study the signaling effects of education for the default risk of borrowers. Three dependent variables are created, namely, the probability of default, overdue payments and overdue amount, and probit models, count models and Tobit models are employed correspondingly. The number of universities in the “211 Project” of China at the city level is employed as the instrumental variable. The empirical evidence shows that education generally plays a strong signaling role in the identification of borrowers’ default risk in China. The negative marginal effect of education declines as borrowing times increase and as the marketization of regions deepens. This study helps to fill an important gap in the existing literature. Platforms and lenders can use educational level for reference in identifying the default risk of borrowers.

Increasing a personal debt burden implies greater financial vulnerability and threats for macroeconomic stability. It also generates a risk of the households over-indebtedness. The assessment of over-indebtedness is conducted with the use of various objective and subjective measures based on the micro-level data. The aim of the study is to investigate over-indebted households in Poland using a unique dataset obtained from the CATI survey. We discuss and compare the usefulness of various over-indebtedness measures across different socio-economic characteristics. Due to the differences in over-indebtedness across single measures, we perform a more complex assessment using a mix of indicators. As an alternative to other commonly criticised over-indebtedness measures, we apply the “below the poverty line” (BPL) measure. In order to obtain the profile of over-indebted households, we use classification and regression tree analysis as an alternative to logit or probit models. We find that DSTI (“debt service to income”) ratio underestimates the extent of over-indebtedness in vulnerable groups of households in comparison with the BPL. We highlight the necessity to use different measures depending on the adopted definition of over-indebtedness. A psychological burden of debts is particularly strong among older and poorly educated respondents. We also find that the age structure of over-indebted households in Poland differs from this structure in countries with a broader access to consumer credits. Our results can be used to enrich the methods of assessing the household over-indebtedness.

Very few empirical studies account for the dynamic nature of the agricultural technology adoption decision and none of these explores if this dynamic nature depends on the gender of the decision maker. Using four waves of a household‐level Ugandan panel data, this is the first empirical analysis to account for self‐learning (one's own adoption experience) in explaining current adoption decision in a developing country context, and the first to study the interaction between self‐learning and gender. Technology adoption is defined as adoption of hybrid seed, inorganic fertilizer, or pesticides. Our results indicate that the dynamic panel data Probit model is superior to its static counterpart in the sense that self‐learning, captured by lagged technology adoption indicators, is by far the most important determinant of technology adoption. We also find a weaker impact of self‐learning for female‐headed households than male‐headed households. Female‐headed households face fewer learning opportunities, which produce a lower self‐learning impact in later periods, further exacerbating the gap in technology adoption among male‐ and female‐headed households.

Purpose The purpose of this paper is to understand the determinants of financial inclusion and the determinants of barriers to financial inclusion in India. Also, the purpose is to ascertain the determinants of informal financial activities in India. Design/methodology/approach The data have been collected from the Global Findex Database (Findex) 2017. Various measures of financial inclusion, namely, ownership formal accounts, use of accounts for saving and borrowing, ownership and use of the debit card are used. The independent variables used are: age, income, education and gender. Given the binary nature of dependent variables, this paper uses the Probit model to draw the inferences. Findings The results show that gender, age, education and income have a significant impact on the various measures of financial inclusion. Additionally, these factors have a significant impact on the informal saving and borrowing. Research limitations/implications The given study uses the deferent measures of financial inclusion. An index of financial inclusion created using all the financial inclusion measures would be a better indicator of financial inclusion. Practical implications The results of this study would be useful for policymakers to identify the determinants and barriers of financial inclusion in India. The results show that policymakers should focus on the female population, in particular, and education and income enhancing measures, in general, to make financial inclusion more inclusive. Originality/value The study is the first of its kind to analyze financial inclusion in India using the Findex. Unlike previous studies, variables such as education and income are constructed more pragmatically. In particular, the study tries to understand the socio-economic determinants of financial inclusion measured as ownership of formal accounts, formal saving, formal credit, ownership of debit cards and use of debit cards. The study also analyzes the determinants of barriers to financial inclusion, savings (formal and informal) and borrowing (formal and informal).

Microfinance is key to reducing poverty in Pakistan. While comprehensive finance is frequently considered as, it creates inclusive growth and poverty reduction in poor communities, and can be boosted by ease of finance. However, when the poor people are involved in the broader scale (different types of poverty level), can this microfinance work? We used an econometric model to test the symmetry approaches of the comprehensive financial organizations and the poor in poverty reduction activities to find the answers. Keeping this in view, we studied different determinants related borrowers for the poverty reduction with respect to access to Micro finance institutes (MFI) and productive loan. Despite some limitations, such as those arising from potential unobservable important determinants of access to MFIs, significant positive effect of MFI productive loans has been confirmed. The significance of “treatment effect” of coefficients has been verified by probit model. In addition, we found that loans for productive purposes were more important for poverty reduction by MFB (Microfinance banks) than MFI. However, in urban areas, simple access to MFIs has larger average poverty‐reducing effects than the access to loans from MFIs for productive purposes. This leads to exploring service delivery opportunities that provide an additional avenue to monitor the usage of loans to enhance the outreach. Therefore, the results showed by probit model that access to MFI was better in urban areas and male borrowers thus achieved more loan. Therefore, it is suggested that for the poverty reduction, there is a dire need to improve and localize the Microfinance institutions in rural areas as well as to promote group lending methodology to avoid risk of getting loans and increase the number of both male and female savers. Thus, the saving value will be increased and side by side interest rate will be significantly achieved. Hence, it is concluded that the goal of providing sustainable financial services implicitly implies that MFIs provide financial services to the poor, whenever they find it profitable to do so. The removal of subsidy and the absence of interest rate restrictions could make the market for the poor become even worse as the market occupiers may act in their own interest. The powerful push will be needed from national economic and social impacts for the increasing support for microfinance.

This paper aims to evaluate the role played by different sources of financing when analyzing firms' attitudes towards innovating. The empirical investigation is based on a large sample of European small and medium‐sized enterprises (SMEs) observed over the period 2012–2017. Different measures of finance and several robustness checks are used to select a well‐behaved probit model. The results show that the probability to innovate increases when firms use internal financing and grants. The same applies when funds come from family and friends, while no conclusive evidence is found for bank loans. Recommendations for public policy to encourage firm‐tailored policies to promote investment in intangibles allow firms to benefit from innovation activities. European SMEs will also benefit from capital market developments and the advancement of new financial tools devoted to supporting innovation.

We empirically examine the predictability of the conditions which are associated with a higher probability of a price spike in agricultural commodity markets. We find that the forward spread is the most significant indicator of probable price jumps in maize, wheat and soybeans futures markets, a result which is in line with the “Theory of Storage”. We additionally show that some option-implied variables add significant predictive power when added to the more standard information variable set. Overall, the estimated probabilities of large price increases from our probit models exhibit significant correlations with the historical sudden market upheavals in agricultural markets.

This study is based on the data of the companies traded on the BIST (Borsa Istanbul Stock Exchange) stock exchange with the panel probit method to obtain the risk of empirical non-payment risk with...

Purpose The purpose of this paper is to investigate whether the probability of deal success/failure in mergers and acquisitions (M&As) transactions is influenced by a range of deal, firm and country-specific characteristics which tend to affect acquirers’ shareholder returns. The specific hypotheses under investigation relate to the method of payment (cash versus stock), target status (listed versus non-listed), diversification (domestic versus cross-border and industry-wide) and acquirers’ prior bidding experience. Additionally, the authors also investigate whether announced deals reflect an expectation about likelihood of deal completion. Design/methodology/approach The authors analyse the probability of deal success/failure in M&As by combining event study and probit regression-based methods. The authors use the standard event study methodology to calculate acquirers’ abnormal returns for up to 10 days before and after the announcement date. In the probit model, the dependent variable is the probability of deal i being failure depending on four sets of explanatory variables: method of payment, target status, diversification and acquirer bidding experience, along with a set of control variables. Findings The findings from event study confirm that market reaction is indifferent to whether announced deals are likely to be successfully completed or not, consistent with the efficient markets hypothesis. However, the results from cross-sectional, cross-country regressions confirm that the aforementioned deal characteristics, as well as certain firm and country level attributes do influence the likelihood of whether an announced deal is subsequently completed or terminated. Originality/value In examining whether the specific characteristics affecting the likelihood that M&A transactions, once announced, will ultimately succeed or fail, it seems natural to ask whether the market reaction at the time of deal announcement reflects an expectation regarding deal completion. This could be associated with specific deal or firm-level characteristics influencing shareholder returns or risk, and represents a unique contribution of this study, over and above the use of a global sample of M&A data. The empirical analysis investigates these issues by using an extensive, global sample of 46,758 M&A transactions from 180 countries and 80 industries, which took place between the years 1977 and 2012.

PurposeThe Indian economy has experienced a boom in outward FDI (OFDI) in 2006. The study aims at exploring the factors that drive the boom in OFDI of Indian firms.Design/methodology/approachThe participation of a firm in OFDI is a two-stage process -first, the decision to internationalization and second, how much to invest. We employ a two-stage model to decompose the effects on the decision to internationalization from effects on how much to invest. The two-stage model has the advantage of allowing us to estimate separately the probability of internationalization by a firm – Pr(OFDI > 0) – and the expected volume of investment, E(OFDI|OFDI > 0). The former is estimated by the probit model and the latter is estimated by the ordinary least square model.FindingsThe study finds that prior experience and institutional advantage can strongly drive the internationalization of Indian multinationals. The study also examines the relative importance of two aspects of prior knowledge – length of prior knowledge and depth of prior knowledge on OFDI of Indian firms. The study finds that the depth of prior knowledge is a must influential driver of OFDI in comparison to its length.Originality/valueThe present study is a novel attempt to investigate, ‘What drives the boom in OFDI from India?’

Using probit regression model on primary data, this study reveals that level of educational qualification, value of asset owned and individual’s monthly income, and being married have a positive an...

This study contributes to the debate on accessibility of higher education in Chile, focusing on both socioeconomic and geospatial dimensions of access to university study. The central question we address in this paper is the following: Does geography (physical distance and neighborhood effects) play a significant role in determining accessibility of higher education in Chile? We use Heckman probit-type (Heckit) models to adjust for selection in the process of completing the trajectory towards higher education – that is, pre-selection, application to study at university, and ultimately admission (or denial) to a higher education institution. The results shows that the geospatial elements have a significant local effect on the student’s application and access to Chilean universities.

Productivity growth emanating from scientific advances offered by biotechnology and other plant breeding initiatives offers great promise for meeting the growing food demand worldwide. This justifies investments in agricultural research and development that have led to the development of stress‐tolerant maize varieties (STMVs) in Africa. While most literature has documented the average impacts of STMVs on productivity, this paper is premised on the fact that benefits from technology adoption are not the same across household. The paper addresses this information gap by examining potential heterogeneity in yield, income, and food security benefits from of adopting STMVs using a sample of 720 maize‐producing households from Tanzania. The dose‐response continuous treatment effect method supported by an endogenous switching probit model was used to estimate the heterogenous impact of STMV adoption on the three outcomes of interest. Results show that, overall, the adoption of stress‐tolerant maize varieties increased maize grain yield by about 1 ton/ha, maize income by about $62/ha. The adoption of STMVs also reduced the propensity to report mild, moderate, and severe food insecurity by 34%, 17%, and 6%, respectively. There are substantial idiosyncratic variations in the productivity, income, and food security effects depending on the scale of adoption, with a higher impact at lower dose levels of adoption. The heterogenous and pro‐poor nature of STMV adoption is also revealed through nonparametric results showing higher productivity benefits among households that are less endowed with wealth and knowledge. These findings underscore the need for further scaling of stress‐tolerant maize varieties for greater impact on the livelihoods of poor small‐scale farmers in Tanzania.