Fractional Probit Model Research Articles

A stringent necessity: addressing fiscal bubbles with fiscal rules in Central and Eastern Europe

ABSTRACT We study the role of public debt sustainability in the implementation of national fiscal rules across 11 Central and Eastern European (CEE) countries. We ask whether episodes of unsustainable surges in public debt, i.e. ‘fiscal bubbles’, lead to adjustments in fiscal frameworks in CEE economies. We model how the costs and benefits of fiscal rules explain why politicians select different levels of fiscal stringency and, crucially, how fiscal bubbles bolster politicians’ willingness to tighten fiscal rules via the perception and social pressure channels. On the empirical side, employing a bubble detection algorithm, we identify episodes of explosive public debt behaviour between 2000 and 2021. Panel fractional probit models reveal that (i) the occurrence of fiscal bubbles increases the propensity of a government to enhance fiscal rule stringency, (ii) the beneficial effects of fiscal bubbles are decreasing in government effectiveness, suggesting that the perception channel likely dominates the social pressure channel.

Interprofessional team-based primary care practice and preventive cancer screening: evidence from Family Health Teams in Ontario, Canada.

Health care reforms introduced interprofessional team-based primary care to optimize access to health care and preventive services. In this context, preventive cancer screening represents an important measure as it is essential for the early detection of cancer and treatment. We investigated the effects of Family Health Teams (FHTs), an interprofessional team-based primary care practice setting, on cancer screening rates in Ontario, Canada. By utilizing comprehensive health administrative data from April 1st 2011 to March 31st 2023, we determined the effect of FHT on screening rates for breast, cervical, and colorectal cancer while controlling for relevant physician and patient characteristics. Our analytical framework employs fractional probit models, including the Mundlak procedure, and generalized estimating equations to assess the impact of practicing in FHTs on cancer screening rates, while accounting for unobserved physician heterogeneity. Our results indicate that compared to non-FHTs, physicians practicing in FHTs have higher breast (2.4%), cervical (2%), and colon (0.8%) cancer screening rates per physician per year. The effectiveness of FHTs in promoting cancer screenings is particularly pronounced in smaller practices and among populations in rural and economically deprived areas. Our findings highlight the role of teams in enhancing preventive health care services potentially through task shifting mechanisms and suggest that such models may offer a pathway to improving access to preventive health care, especially in marginalized populations. Our research contributes to the literature by providing empirical evidence on the benefits of interprofessional team-based primary care in improving cancer screening.

Governance and information technology for female labour force participation in the African Continental Free Trade Area

The motivation of the present study is to complement the extant literature by assessing the relevance of governance and information technology in how African trade affects female labour force participation. The study focuses on 48 African countries using data for the period 1996–2021. An adopted empirical strategy is the fixed effects regressions that are designed to address concerns for simultaneity and the unobserved heterogeneity. The fractional probit model based on the pooled Bernoulli quasi-maximum likelihood method is also employed. The following main findings are established. First, governance moderates intra-African trade to engender positive synergies on female labour force participation. The positive synergies are apparent from the overall quality of institutions, government effectiveness and the rule of law. Second, information technology does not significantly moderate intra-African trade to affect female labour force participation. The established findings from fixed effects regressions are robust to fractional probit model estimations. The findings are relevant in informing policy makers on how governance can be used to moderate the influence of African trade in promoting female labour force participation. Policy implications are discussed.

Calf mortality in Turkish dairy farms: Economic impact, regional disparities, and farm-level drivers

This study investigates the economic burden of calf mortality in Turkish dairy farms and its impact on the national economy. We gathered research data by directly surveying dairy farms in seven provinces, each representing a distinct region of Turkiye. By conducting these surveys, we captured data on various aspects of calf mortality, including losses among non-pregnant cows aged two and older, pregnant cows, and those experiencing complications during birth, as well as losses within the 0–6 month age bracket. These figures were then amalgamated to establish the overall calf loss rate. Using a fractional probit model, we examined the empirical relationship between total calf loss rates and the socio-demographic characteristics of farm operators and their establishments. Our findings revealed that approximately 82 % of farms experienced some degree of calf loss, with the calf loss rate among dairy cattle farming accounting for nearly 20 %. Notably, regional disparities emerged as a key observation, alongside the identification of certain socio-demographic farm characteristics that proved statistically significant. Specifically, factors such as the prevalence of local cattle breeds, the proportion of crossbred bulls, as well as the numbers of heifers and calves, stood out as influential. Further scrutiny, fortified by ANOVA tests and relationships between the number of cows and total calf loss rate, underscored pronounced geographical disparities in post-estimation calf loss rates. Meanwhile, correlation heatmaps illuminated noteworthy relationships between specific cattle traits and the extent of calf losses. These findings not only underscore the severity of the issue but also highlight the urgency of preventive measures. In light of these insights, we offer pertinent policy recommendations to stakeholders and policymakers aimed at mitigating this considerable economic burden effectively.

Unwelcomed guests: Impact of deer harvest on corn and soybean wildlife damage

While wildlife damages are a relatively small part of crop insurance claims in the United States, reported damages from wildlife are growing and producers are concerned this issue is getting worse. Wildlife agencies advocate for hunting as a control to wildlife damages to crops but to our knowledge, no study has econometrically explored if hunting could reduce crop damage. Therefore, we analyze if county-level white-tailed deer (Odocoileus virginianus) harvest and other factors like habitat and field fragmentation are associated with corn and soybean acres being indemnified due to wildlife damages in Tennessee. We estimate a fractional probit model using crop insurance data to measure crop damages and a county-level white-tailed deer harvest dataset. We find a higher coverage level of a policy increases the likelihood of both corn and soybean acres being indemnified due to wildlife damage. We also find white-tailed deer harvest during the period post-harvest in the previous crop year (November through January) slightly decreases the likelihood of a claim being made due to wildlife damage for corn but was not found to mitigate losses to soybeans. The whitetail hunting season appears to align better with corn production to reduce crop losses than with soybeans. This study will be useful for wildlife and crop agencies in state and federal governments to develop policies to more effectively utilize hunting to reduce crop insurance claims from wildlife damages.

Information Technology and Governance: Does E-governance Aid Budget Transparency?

Advancement in information and telecommunication technologies (ICTs) has helped open governance to public participation. The participation of the citizens in government is essential for transparent and sustainable governance. This study examines the relevance of e-governance in promoting transparency and accountability concerning the government’s fiscal activities. The study, employing the variation in the open budget index using the fractional probit model, finds that the adoption and use of e-governance enhance and promote budget transparency. This evidence conforms with governments’ growing adoption of ICTs in serving and communicating their fiscal activities to the public.

Is Green Transition in Europe Fostered by Energy and Environmental Efficiency Feedback Loops? The Role of Eco-Innovation, Renewable Energy and Green Taxation

Green transition is in the core of the European policy agenda to achieve the ambitious goal of climate neutrality following the launch of the European Green Deal. The cornerstone of the new growth strategy of Europe is resource efficiency which focuses on shifting to a more sustainable production paradigm by conserving scarce resources and by prioritizing enhanced environmental performance. Scattered efforts to investigate the drivers of resource efficiency measures have shed light on the key drivers, however, those consider resource efficiency measures in isolation neglecting for feedback loops influencing green transition. Therefore, we develop a conceptual framework to study green transition as a system of resource efficiency measures affected by feedback loops, path dependence, green technologies, and green policy tools. We mobilize the analysis by devising a unique balanced panel covering the EU-28 from 2010 through 2019, including policy efforts paving the way for green transition. Econometric results based on a system of fractional probit models, indicate that resource efficiency measures are intertwined via feedback loops, especially in the case of environmental efficiency. Green technologies affect green transition, however, rebound effects emerge in the case of energy efficiency. Past performance affects current levels pushing towards divergence. Evidence suggests that green taxation fosters energy efficiency whereas hinders environmental efficiency. The asymmetric operation of feedback loops and green taxation on energy and environmental efficiency highlights that horizontal policies hinder rather than foster green transition. This study contributes to SDGs 7, 12, 13 and 16.

Nexus between participation in nonfarm enterprises and poverty among rural farm households: evidence from Nigeria

PurposeDespite a reduction in poverty the global population in 2015, the incidence of poverty remains very high in Sub-Saharan African countries. Most of the countries in the region are agrarian, with most of their population residing in rural areas, and a majority of the poor in the region are found in Nigeria. This study examined the nexus between participation in nonfarm enterprises (NFEs) and poverty among rural farm households in Nigeria and across the six geopolitical zones.Design/methodology/approachThe Nigerian Living Standard Survey (NLSS) conducted in 2018–2019 by the National Bureau of Statistics was used. We made use of 13,440 farm households with useful information for the purpose of this study. The sample comprises 6,885 households that participated in NFEs and 6,555 nonparticipating households. The data were analyzed with Foster, Greer, and Thorbecke (FGT) (1984) metrics, probit, and fractional probit models at p = 0.05.FindingsThe incidence of poverty was lower among the participating households than in the nonparticipating households. Participation in NFEs had a mitigating effect on poverty. We also established that zonal differentials in poverty rates exist among households in all the analyses. Participation in NFEs was influenced by individual, household, and institutional factors and was also able to explain the depth of poverty among the respondents.Practical implicationsIt is suggested that poverty alleviation policies should be targeted at improving access to nonfarm economic activities by rural farm households residing in vulnerable geopolitical zones.Originality/valueThis study is the first attempt to profile household poverty based on the type of NFEs they are involved in. The study also provides an insight into the effect of the state of residence on zonal poverty models, which is expedient if the country must achieve Sustainable Development Goal 1 on the eradication of poverty everywhere.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0493

A multi-dimensional assessment of financial hardship of cancer patients using existing health system data.

Existing financial hardship screening does not capture the multifaceted and dynamic nature of the problem. The use of existing health system data is a promising way to enable scalable and sustainable financial hardship screening. We used existing data from 303 adult patients with cancer at the University of Virginia Comprehensive Cancer Center (2016-2018). All received distress screening and had a valid financial assistance screening based solely on household size-adjusted income. We constructed a composite index that integrates multiple existing health system data (Epic, distress screening, and cancer registry) to assess comprehensive financial hardship (e.g., material conditions, psychological responses, and coping behaviors). We examined differences of at-risk patients identified by our composite index and by existing single-dimension criterion. Dynamics of financial hardship over time, by age, and cancer type, were examined by fractional probit models. At-risk patients identified by the composite index were generally younger, better educated, and had a higher annual household income, though they had lower health insurance coverage. Identified periods to intervene for most patients are before formal diagnosis, 2 years, and 6 years after diagnosis. Within 2 years of diagnosis and more than 4 years after diagnosis appear critical for subgroups of patients who may suffer from financial hardship disparities. Existing health system data provides opportunities to systematically measure and track financial hardship in a systematic, scalable and sustainable way. We find that the dimensions of financial hardship can exhibit different patterns over time and across patient subgroups, which can guide targeted interventions. The scalability of the algorithm is limited by existing data availability.

Portfolio allocation and borrowing constraints

Using the US Survey of Consumer Finances, we explore the empirical relationship between borrowing constraints and financial portfolio allocation by American households. To help motivate our empirical analysis we initially draw insights from a mean-variance model of optimal portfolio allocation with three tradable asset classes defined by increasing risk, and establish a link between borrowing restrictions and portfolio allocation in the presence of background risk. Our main contribution, however, lies in estimating the role that borrowing constraints play in shaping households' financial portfolio allocation. This is achieved using an ordered fractional probit model. In addition to revealing the significant empirical role played by household borrowing constraints in determining portfolio allocation, our analysis helps us to resolve ambiguity surrounding the behaviour of the medium-risk asset in our motivational theoretical framework. Further, the empirical distribution of medium-risk assets is found to be remarkably similar to that for high-risk assets, suggesting the presence of a more general ‘risk puzzle’, which our borrowing constraints measures partially explain.

Effects of disability on income and income composition.

Income composition is highly associated with individual financial sustainability and income inequality at the macro level. Although studies have investigated the effects of disability on wage income, few studies have investigated the effects of disability on income composition or on various types of income other than wage income. We sampled 72,000 households using tax data sourced from the Taiwan Ministry of Finance in 2015. Data for each household member were traced back to 1999. We identified 23,346 individuals with disabilities and matched them with 34,145 individuals without disabilities. Eight income types were identified. A two-way fixed-effect analysis was performed to determine the effects of disability on changes in each income type. Fractional probit models were estimated to determine the effects of disability on the proportion of each income type in total income at different ages. Wage income constitutes the largest proportion of income in Taiwan. The total income is estimated to increase by 10.4% (P < 0.001) after disability onset. Moreover, most income categories did not experience a decline following the onset of disability. We also noted a significant interaction effect between disability status and age on the proportion of each income type in total income. The effect of disability on income varied across different sources of income. The income composition observed for the individuals with disabilities changed considerably at various ages. Accordingly, policies should be designed to ensure long-term sustainability of income sources for individuals with disabilities.

Graduate employment: Does the type of higher education institution matter?

AbstractThe paper analyses whether the type of institution from which students graduate has an impact on their unemployment propensity. It uses official data on the Portuguese higher education system, for 2018, at the program/institution level, which provides information on graduate unemployment, as well as demographic and socioeconomic background information. A fractional probit model on graduates’ propensity for unemployment is estimated. Results suggest that polytechnic graduates face higher unemployment propensity than university graduates, maintaining inequalities present in students’ previous trajectories. Policies targeting socioeconomic segregation need to address not only access to higher education but also the transition to the labor market.

Ownership Structure and Information Disclosure in Sub- Saharan African Countries

Purpose: This study examines the association between ownership structure and information disclosure using a sample of the listed non-financial firms in Sub-Saharan African countries.&#x0D; Design/Methodology/Approach: This study employed quantitative methods to examine the relationship between ownership structure and information disclosure. The population was non-financial firms listed in eleven countries in Sub-Saharan Africa. Data were sourced from the listed firms’ annual reports available online. The regression analysis was done using the fractional probit model. The dependent variable is the disclosure index which was developed using scores of various attributes of information disclosure through analysis of annual reports to identify whether the attributes were included in the annual reports. The firm scored 1 if the attribute was included in the annual report and zero otherwise. Thereafter, the scores were aggregated to obtain actual scores for each individual firm. Finally, the average score was computed by dividing aggregated actual score value by the expected score value.&#x0D; Findings: Findings indicate that concentrated ownership is significantly negatively associated with disclosure. Furthermore, the findings show government and foreign ownerships are positively and significantly associated with information disclosure. This study shows the effects of ownership structure on disclosure. Overall, the findings indicate that ownership structure is related to information disclosure.&#x0D; Research Limitation/Implication: This study focused on non-financial listed firms which their annual reports were available online. The interpretation of the results of these studies needs to consider this bias as may affect the generalizability of the results to all firms including those which do provide annual reports online.&#x0D; Practical Implications: The finding implies reforms should consider the presence of different characteristics of firms, in particular ownership structure, and their impacts on the firm propensity to disclose information.&#x0D; Social Implications: More specifically, the finding suggests that applying simple policies to specify types and levels of disclosure requirements to all firms may not be realistic because the concept of one size fits all may not be applicable.&#x0D; Originality/Value/Novelty: The study provides highlights on determinants of information disclosure which is one of the mechanisms for monitoring agency problems resulting from the conflict of interests between internal and external stakeholders of the firm. In this regard, this study extends research on the nexus of ownership structure and information disclosure to developing countries’ context and therefore contributes to understanding corporate governance around the globe.

BAYESIAN SEMIPARAMETRIC LONG MEMORY MODELS FOR DISCRETIZED EVENT DATA.

We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence. This rules out Poisson process based models where the rate function itself is not long range dependent. The proposed class of FRActional Probit (FRAP) models is based on thresholding, a latent process. This latent process is modeled by a smooth Gaussian process and a fractional Brownian motion by assuming an additive structure. We develop a Bayesian approach to inference using Markov chain Monte Carlo and show good performance in simulation studies. Applying the methods to the Amazon bird vocalization data, we find substantial evidence for self-similarity and non-Markovian/Poisson dynamics. To accommodate the bird vocalization data in which there are many different species of birds exhibiting their own vocalization dynamics, a hierarchical expansion of FRAP is provided in the Supplementary Material.

The decline of part-time farming in Europe: an empirical analysis of trends and determinants based on Eurostat panel data

ABSTRACT This article studies the state of part-time farming in the European Union (EU) amidst recent developments in its agricultural structure. First, an in-depth descriptive analysis of the trends in farm other gainful activities (OGA) is delineated. Second, an econometric panel regression analysis employing fractional probit model is conducted to investigate the relationship between the share of OGA and different farmer and farm characteristics. The analysis utilizes a balanced panel of 27 EU countries extracted from the Eurostat database between 2005 and 2016. The results show that OGA as main activity significantly decreased between 2005 and 2016, whereas the proportion of sole holder-managers with OGA as secondary activity slightly increased. OGA are explained by economic needs and are mostly related to farm size and farm types with lower economic farm productivity. The main OGA are mainly related to farmer characteristics (e.g. age and gender). Secondary OGA are explained by farm specialization. These trends may continue into the future which may bring an even fewer number of larger, more specialized, and more professional farms that have little time to engage in other activities than their core business of farming.

Servicification and manufacturing exports: Evidence from India

This paper studies whether services inputs can promote exports of manufacturing firms in India, given that the country is recognized for its services sector. There is growing evidence of servicification of manufacturing firms since services are useful in overcoming informal barriers and facilitating trade. Using data for science-based manufacturing firms over the period 2001–2016, we study the impact of servicification on export intensity, using a fractional probit model. The results indicate that by raising the share of services as inputs, the export intensity of firms rises after controlling for firm covariates such as size, exporter status and MNE status. The results hold true even after endogenizing TFP. The study finds new firm-level evidence on the key role played by services in manufacturing exports and provides recommendations for framing policies conjointly for the manufacturing and services sectors.

Evaluating livestock farmers knowledge, beliefs, and management of arboviral diseases in Kenya: A multivariate fractional probit approach.

Globally, arthropod-borne virus (arbovirus) infections continue to pose substantial threats to public health and economic development, especially in developing countries. In Kenya, although arboviral diseases (ADs) are largely endemic, little is known about the factors influencing livestock farmers' knowledge, beliefs, and management (KBM) of the three major ADs: Rift Valley fever (RVF), dengue fever and chikungunya fever. This study evaluates the drivers of livestock farmers' KBM of ADs from a sample of 629 respondents selected using a three-stage sampling procedure in Kenya's three hotspot counties of Baringo, Kwale, and Kilifi. A multivariate fractional probit model was used to assess the factors influencing the intensity of KBM. Only a quarter of the farmers had any knowledge of ADs while over four-fifths of them could not manage any of the three diseases. Access to information (experience and awareness), income, education, religion, and distance to a health facility considerably influenced the intensity of farmers' KBM of ADs in Kenya. Thus, initiatives geared towards improving access to information through massive awareness campaigns are necessary to mitigate behavioral barriers in ADs management among rural communities in Kenya.

Participating to Compete: Do Small Firms in Developing Countries Benefit from Global Value Chains?

Standard trade theory suggests that the profile of exporting firms is characterized by large firms which dominate domestic productivity distribution. Large manufacturing multinationals have increased their productivity by participating, creating and shaping global production networks. In recent decades, trade flows have become increasingly dominated by trade-in-tasks within global production networks. Given the importance of pro-competitive effects in establishing the gains from trade following trade liberalizations, it is important to look at the link between participation in global value chains and a firm’s competitiveness. The paper does so by using the International Trade Centre’s competitiveness index, for small, medium-sized and large firms, coupled with global value chain participation measures extracted from multi-regional input-output tables, and together forming a panel dataset at country and firm category level. The main finding establishes that the gains from integration into value chains are greater for small firms than for large firms. In particular, at the sample median, an increase of participation by 2.5% reduces the competitiveness gap between small and large firms by 1.25%. In addition, the analysis suggests that it is the use of foreign inputs that drives the result. In contrast, the domestic value in intermediate goods matters only in cases where value chains respond to domestic demand needs. The identification strategy relies on a fractional probit model allowing for unobserved effects, and a causal framework using the depth of trade agreements as instrument, in order to mitigate potential reverse causality.

Urban-rural divide in foodborne illness in China: what can we learn from the socioeconomic factors?

Background China’s urban-rural divide, though still improving, can be seen from various sectors of the economy. The objective of this study is to explore how socioeconomic factors in and across both urban and rural areas explain the occurrence of foodborne illness in China. Over the last decades, food safety laws and regulations have been established in China, but more understanding about the food safety issues are needed in order to eliminate food safety hazards. Methods This study intends to estimate several panel data models in econometrics to obtain the average partial effects of many socioeconomic factors in and across urban and rural areas on per capita foodborne incidents and patients, respectively. Given the fractional nature of the two dependent variables, fractional probit models are estimated using both the Quasi Maximum Likelihood Estimation (QMLE) and the bootstrap Generalized Estimating Equations (GEE) approaches in addition to the standard estimation of panel data random effects, fixed effects, and Tobit models. China official data on foodborne incident and patient cases in each province and in each year from 2011 to 2018 are obtained from various issues of the China Health Statistical Yearbook. Additional data on 19 socioeconomic variables are obtained from various issues of the China Statistical Yearbook. Results The main results show that socioeconomic factors such as owning TVs, owning refrigerators, consumption expenditures and household income in urban or rural areas explain the per capita foodborne incidents or per capita foodborne patients differently, reflecting differences in people’s food safety awareness, food storage patterns, food markets, and income effects in the urban and rural areas. Socioeconomic factors such as urbanization and primary industry’s share of the gross regional product across areas tend to worsen the food safety problem. Improving regional economies and increasing government spending on public health could reduce the occurrence of foodborne illness. Conclusions It is suggested that governments take into account the social disparities of urban and rural areas when designing and implementing food safety policies. It is also suggested that a holistic approach is needed to resolve food safety issues by combining food safety control and management policies with soil and water management policies.

FIRMS’ EXPORT PERFORMANCE: A FRACTIONAL ECONOMETRIC APPROACH

Export activities have become crucial to firms’ competitiveness, with determinants of export performance being a challenging field of research, since there is no consensus regarding the explained and explanatory variables or on the econometric methods to be used. Using a panel data of Portuguese wine firms, this paper aims to contribute to this debate, combining both resource- and institutional-based views of the firm. This paper tries to overcome the methodological hurdle, addressing sample selection issues and considering the fractional response nature of export performance. Given the pros and cons of each econometric approach, the Heckman selection model, the fractional probit model and the two-part fractional response model are estimated, and the results compared. From a public policy perspective, the results show that policies that promote wine firm size, labor productivity and wine promotion in third countries have a positive impact on export performance at firm-level. Age does not appear as a key factor on the internationalization of Portuguese wine firms