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While a lot has been written on the socio‐economic and welfare impacts of agricultural technologies, there has been a bias toward crop production systems to the neglect of improved livestock production methods and technologies. This paper explores the welfare impacts of improved livestock production practices and technologies using data from a low‐income country. Using an econometrics technique that corrects selection bias, the paper shows that the adoption of improved livestock production practices has a positive impact on household welfare, measured by consumption expenditure and diet quality. The study also identified increased consumption of animal source foods, reducing animal death and income from the sale of animals as potential mechanisms through which such improvements in livestock production affect family welfare. [ABSTRACT FROM AUTHOR]

The research delt with the effect of labour out-migration on output per hectare and efficiency of wheat and teff producers in Kembata-Tembaro and Hadiya zones of Ethiopia based on primary data gathered from 415 random sample of rural households. The multinomial endogenous switching model was used as an analytical model. According to the stochastic frontier model, the mean efficiency of wheat and teff are 82.98 and 66.43 per cent, respectively. According to the econometric results, rural–urban and international migration reduces wheat productivity by 110.94 and 179.11 kg, respectively. The average treatment effect on treated (ATT) also revealed that participation in international migration reduces Teff producers' technical efficiency by 5.51 per cent. However, teff productivity is reduced by 382.94 and 747.49 kg due to rural urban and international migration, respectively. The lost labour channel of the modern theory of migration is maintained by the result of the study. So as to minimise the negative impact of out-migration in the study area, policymakers must focus more on promoting access to credit, irrigation, land, off-farm employment and public services for rural households. [ABSTRACT FROM AUTHOR]

Declining land productivity and increasing land and food scarcity, amidst high population growth have precipitated the need for intensification of crop production. Sustainable land management technologies (SLMTs) have been suggested as a way to support the intensification process. In Uganda, agricultural advisory services (AAS) geared towards improved adoption of the SLMTs are provided, and farmers can access AAS from diverse sources, with the possibility of accessing from single or multiple sources. This study attempts to identify and prioritize the drivers of farmers’ access to (single/multiple) sources of AAS and determine the impact of access to these sources of AAS on the adoption of SLMT, and crop productivity. The study uses cross-sectional data collected from 435 households in the southwestern highlands of Uganda, in Kisoro and Kabale districts. The multinomial endogenous switching regression model combined with an endogenous switching regression model was used to analyse the data. Results indicate that both single and multiple sources of AAS have a positive effect on adoption of SLMTs and crop productivity, with the latter having a positive effect on the adoption of more SLMTs, while it seems to reduce the adoption of some other SLMTs. Similarly, accessing AAS from multiple sources has a higher positive impact on crop productivity, when compared to no access, but a lower impact when compared to access to a single source of AAS. These results suggest that access to multiple sources of AAS has positive impacts, but there are possible inherent challenges in the way it is implemented; lack of synchronisation of the messages given to the farmers, and the top-down approaches used to disseminate knowledge on SLMTs by some of the AAS providers may confound the possibly higher benefits of access to multiple sources of AAS. This study points out the need for policy to consider the advantages of having a streamlined agricultural extension system, with coordinated efforts from all agricultural advisory service providers and stakeholders. [ABSTRACT FROM AUTHOR]

AbstractThis study examined the impact of rural out-migration on the poverty of migrant-sending households by applying the new economics labor migration theory as a theoretical framework, and the multinomial endogenous switching regression as an analytical model in southern Ethiopia. Data were gathered from 415 sample rural households using stratified random sampling in the year 2021. The cost of basic needs approach and the Foster, Greer, and Thorbecke (FGT) method were used to establish the poverty line and create the poverty indices, respectively. The average annual food and non-food poverty lines are Birr 8997.52 and 2249.38 per adult equivalent. The incidence, depth, and severity of general poverty are 39.76, 10.11, and 3.55%, respectively, while the incidence, depth, and severity of food poverty are 34.70, 9.47, and 3.58%, respectively. When compared to other households, households with international migrants have a lower incidence, depth, and severity of poverty. The regression result of the multinomial endogenous switching model showed that international migration increases consumption per adult equivalent of households by 29.8% and is significant at the 1% level. Participation in rural-urban and international migration increases kilocalories per adult equivalent per day by 7.4 and 36.4%, respectively, in migrant-sending rural households. The findings support the new economics labor migration theory’s remittance hypothesis. Promoting access to land, capital, farm and non-farm employment, irrigation, family planning, and basic public services would improve rural household welfare and reduce the current wave of rural out-migration in Southern Ethiopia.

Abstract This study examines the earnings differential between users and non-users of networks of Indonesian internal migrants. By exploiting the Indonesian Family Life Survey wave 5, we employ endogenous switching regression to handle the self-selection bias in the model. We find evidence that the inherent characteristics of the migrants create a tremendous earnings gap between the two agents. Users of networks experience a wage penalty compared to non-users of network. We also find that education has a dominant impact on increasing the earnings discrepancy for migrants. These suggest that network users find it difficult to catch up on the earnings of their non-user counterparts. In addition, the study reveals that networks are not necessarily the only influencing factor of earnings differential. Moreover, the study specifically suggests that hiring channel through networks supports migrants in securing employment. However, the low education levels of the migrants restrict them from enjoying higher earnings. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to assess the estimability of the proposed model, referred to as the mixed semipara-metric switching meta-regression model. The model is expressed as a Generalized Additive Model (GAM), which accommodates a high- dimensional set of covariates not usually considered in metadata. Furthermore, the applicability of the mixed semiparametric switching meta-regression model in meta-analysis settings is established in this study. [ABSTRACT FROM AUTHOR]

Though few studies have examined the impact of rural–urban migration on a unidimensional measure of welfare, evidence on the impact of rural–urban and international migration on vulnerability to rural multidimensional poverty of households is undocumented. This study examined the impact of rural–urban and international migration on vulnerability to rural multidimensional poverty by applying the new economics labor migration theory as a theoretical framework, and the multinomial endogenous switching regression as an analytical model. Primary data were gathered from samples of 415 households using stratified random sampling in southern Ethiopia in the year 2021. The descriptive results showed that the incidences of rural multidimensional poverty and vulnerability to rural multidimensional poverty of households are 72.3 and 84.10% respectively in the study area. The average vulnerability of households with international migrants is significantly lower by 6.33% compared to households without migrants while the average rural multidimensional poverty of households without migrants is significantly higher by 15.71% compared to households with international migrants. Likewise, the average rural multidimensional poverty of households with rural–urban migrants is significantly higher by 17.34% compared to households with international migrants. The regression result of the multinomial endogenous switching model revealed that participation in international migration reduces rural multidimensional poverty and vulnerability by 34.32 and 12.33% whereas participation in rural–urban migration reduces rural multidimensional poverty and vulnerability by 20.63 and 11.42% respectively. As well, participation in rural–urban and international migration significantly increases kilocalories per adult equivalent per day of households by 29.32 and 53.17% respectively. The result supports the remittance hypothesis of the new economics labor migration theory. Hence, improving access to capital, agricultural land, and viable on-farm and non-farm employment by rural households would reduce both ex-post and ex-ante poverty of households and minimize the current wave of youth out-migration in southern Ethiopia. [ABSTRACT FROM AUTHOR]

This study examines the impact of the row planting method on maize productivity and risk exposure using panel datasets from Ethiopia. A flexible moment-based production function is fitted to capture the expected yield, yield variance, and exposure to downside risk. A Mundlak–Chamberlain approach is combined with a switching regression treatment effects model to account for unobserved heterogeneity and endogeneity. The study shows that adopters of the row planting method significantly reduced exposure to downside risk while increasing expected yield. The analysis also identified some household and environmental conditions that affect the gain from the row planting method. [ABSTRACT FROM AUTHOR]

This study examined the impact of rural out-migration on the poverty of migrant-sending households by applying the new economics labor migration theory as a theoretical framework, and the multinomial endogenous switching regression as an analytical model in southern Ethiopia. Data were gathered from 415 sample rural households using stratified random sampling in the year 2021. The cost of basic needs approach and the Foster, Greer, and Thorbecke (FGT) method were used to establish the poverty line and create the poverty indices, respectively. The average annual food and non-food poverty lines are Birr 8997.52 and 2249.38 per adult equivalent. The incidence, depth, and severity of general poverty are 39.76, 10.11, and 3.55%, respectively, while the incidence, depth, and severity of food poverty are 34.70, 9.47, and 3.58%, respectively. When compared to other households, households with international migrants have a lower incidence, depth, and severity of poverty. The regression result of the multinomial endogenous switching model showed that international migration increases consumption per adult equivalent of households by 29.8% and is significant at the 1% level. Participation in rural-urban and international migration increases kilocalories per adult equivalent per day by 7.4 and 36.4%, respectively, in migrant-sending rural households. The findings support the new economics labor migration theory's remittance hypothesis. Promoting access to land, capital, farm and non-farm employment, irrigation, family planning, and basic public services would improve rural household welfare and reduce the current wave of rural out-migration in Southern Ethiopia. [ABSTRACT FROM AUTHOR]

This paper presents a robust method for dealing with switching regression problems. Regression models with switch-points are broadly employed in diverse areas. Many traditional methods for switching regressions can falter in the presence of outliers or heavy-tailed distributions because of the modeling assumptions of Gaussian errors. The outlier corruption of datasets is often unavoidable. When misapplied, the Gaussian assumption can lead to incorrect inference making. The Laplace distribution is known as a longer-tailed alternative to the normal distributions and connected with the robust least absolute deviation regression criterion. We propose a robust switching regression model of Laplace distributed errors. To advance robustness, we extend the Laplace switching model to a fuzzy class model and create a robust algorithm named FCL through the fuzzy classification maximum likelihood procedure. The robustness properties and the advance of resistance against high-leverage outliers are discussed. Simulations and sensitivity analyses illustrate the effectiveness and superiority of the proposed algorithm. The experimental results indicate that FCL is much more robust than the EM-based algorithm. Furthermore, the Laplace-based algorithm is more time-saving than the t-based procedure. Diverse real-world applications demonstrate the practicality of the proposed approach. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 is a deadly disease that globally infected millions of people. It enormously increases economies national healthcare bills and death tolls that deprive the global world. The negative environmental externality further strains the country's healthcare sustainability agenda, causing to decline in global income. The study evaluates the different socio-economic and environmental factors to assess ecological complexity in a large, cross-country data set that includes 60 countries. The study used the following variables for estimation, i.e., coronavirus cases, cost of carbon emissions, per capita economic growth, foreign direct investment inflows, and population growth. Markov Switching Regression, VAR Granger causality and variance decomposition analysis applied on the given dataset. The results show that the COVID-19 cases have a rebound effect on environmental quality. Economic activities started after a lifted lockdown, and unsustainable production and consumption led to a deteriorating natural environment. The U-shaped relationship is found between carbon pollution and per capita income. On the other hand, the inverted U-shaped relationship is found between coronavirus cases and carbon pollution. The foreign direct investment inflows and population density increases carbon pollution. The study concludes that stringent environmental policies and incentive-based regulations help to minimize coronavirus cases and mitigate carbon pollution. [ABSTRACT FROM AUTHOR]

Many scholars examined and immensely found significant causal relationship present between access to finance and firms’ productivity. However, limited studies and inconclusive generalizations are still pervasive regarding co-existing nexus between financial access in form of overdraft facilities offered by financial institutions toward productivity of manufacturing firms in the Philippines. In addition, cross-country differences related to business environment, income levels, size and depth of the financial system, financial frictions and legal constraints potentially exposing model estimations to simultaneity issues. Thus, this study extends the empirical examination of financeled productivity growth assumptions and expands the application of econometric modelling through instrumental variable regression models using an enterprise survey conducted in 2015 by the World Bank among selected manufacturing firms in the Philippines. The main findings revealed the positive and significant impact of financial access through acquisition of overdraft facilities in enhancing manufacturing firms’ productivity proxied by real annual sales. Meanwhile, other firmrelated factors such as R&D and capital intensities were also found to have significant influence on productivity of manufacturing firms. These results signal practical implications highlighting managers consideration in the inclusion of overdraft facilities as an alternative source of funding for their financing strategies alongside proper resource allocation and management of technology and capital structure, which will provide an avenue for firms to achieve the desired level of productivity growth. However, lack of empirical evidence was found regarding the significant contribution of financial access on productivity when proxied by measures of TFP. [ABSTRACT FROM AUTHOR]

We conduct an exploratory study using a customized Facebook application to understand how social ties are linked to an economic measure of trust. We employ the Investment Game, a well-established economic game designed to generate a quantifiable trust measure. We consider the relationship between observed trust and three “revealed preference” tie strength measures: (1) the degree of interaction between friends on their walls; (2) embeddedness, a metric related to the number of mutual friends shared; and (3) being tagged together in a photograph, indicative of a physical-world interaction. We identify latent heterogeneity among our subjects, establishing that for users with a large number of Face book friends, the only measure associated with trust is whether the dyad was tagged in a photo together. In contrast, for users that are more selective and have fewer Facebook friends, all three aforementioned tie strength measures correlate with trust. Our findings are preliminary evidence that traditional measures of dyadic trust like embeddedness which are used widely in physical-world social networks may not always be effective predictors of digital trust, because not all online social ties are created equal. Our findings provide preliminary evidence that traditional measures of dyadic trust may not always be effective predictors of trust, as not all online social ties are created equal. [ABSTRACT FROM AUTHOR]

The slow recovery of many developed economies to the recent financial crisis, and the largest fall in aggregate demand since WWII caused by the COVID-19 Pandemic with its foreseeable negative and persistent effects on the aggregate supply, has generated renewed interest in the subject of hysteresis. The presence of significant hysteresis effects has important theoretical and policy implications. First, there is no unique and predetermined long-run equilibrium level of aggregate employment, as the equilibrium is permanently changed by temporary shocks. Second, as the economic system is not self-adjusting, substantial, timely, and sustained expansionary monetary and fiscal policy should be applied to mitigate the impact of shocks, including the temporary ones. Although it is not possible to quantify hysteresis effects in real time, we can use historical data to shed some light on the possible long-term economic consequences of the COVID-19 pandemic. For that purpose, we use the linear play-hysteresis model in the context of two equation system to analyses the join hysterical dynamics of aggregate employment and investment. We implement the model empirically by means of a new algorithm for the simultaneous equations system applied to Portuguese data that separates the effects of large and small changes in aggregate demand on aggregate employment and investment using an endogenous determined switching parameter as reference. [ABSTRACT FROM AUTHOR]

The paper assesses the potential impact of the adoption of improved cassava varieties on yields of smallholder farmers. Agricultural intensification is associated with increasing yields per hectare through the use of improved varieties. Studies have established the relationship between adoption and yield, yet this relationship is understudied in the cross-national literature. Using cross-sectional data collected from a randomly selected sample of 1,176 farmers dispersed across Ghana and employing an endogenous switching regression model, the causal impact of improved variety adoption was estimated. Our results revealed that adoption decisions were conditioned by age, extension access, extension visits, awareness and farm size. Also, adoption had a significant positive impact on cassava yields. Adopters had 18 t/ha increases in yields and non-adopters should they have adopted had increases of 10 t/ha. Strategies to resource research extension linkage system to promote and create awareness about the existing improved cassava varieties for increased adoption are recommended.

The improper allocation of economic and environmental resources damages the United Nations sustainable development Agenda, which remains a challenge for policymakers to stop the rot through efficient governance mechanisms. The study designed an efficient environmental governance framework by extending the different governance factors linked to the environmental sustainability ratings in the cross-section of 67 countries. The results of the two-regime based estimator show that environmental corruption (regime-1), environmental politics (regime-2), and environmental laws (regime-2) negatively correlated with the environmental sustainability rating, whereas environmental democracy (regime-1 & 2) positively correlated with the environmental sustainability agenda across countries. The government effectiveness and the country's per capita income both escalates environmental sustainability ratings. The results align with the Demopolis theory, the effective regulatory theory, and the theory of law and politics. The causality estimates show that environmental corruption and government effectiveness causes environmental politics and economic growth. In contrast, environmental democracy and environmental regulations cause a country's per capita income. The bidirectional causality is found between environmental regulations and environmental corruption on the one hand, while environmental regulations and environmental politics Granger cause each other on the other hand. The results show the importance of environmental regulations in managing ecological corruption and politics across countries. The variance decomposition analysis suggested that environmental politics likely influenced the environmental sustainability agenda, followed by government effectiveness and environmental democracy for the next ten years. The study emphasized the need to design an efficient environmental governance framework that minimizes environmental corruption and enables them to move towards environmental democracy, stringent environmental laws, and regulations. Government effectiveness would mainly be linked to reducing corruption and political instability to achieve clean, green and sustainable development. [ABSTRACT FROM AUTHOR]

The paper assesses the potential impact of the adoption of improved cassava varieties on yields of smallholder farmers. Agricultural intensification is associated with increasing yields per hectare through the use of improved varieties. Studies have established the relationship between adoption and yield, yet this relationship is understudied in the cross-national literature. Using cross-sectional data collected from a randomly selected sample of 1,176 farmers dispersed across Ghana and employing an endogenous switching regression model, the causal impact of improved variety adoption was estimated. Our results revealed that adoption decisions were conditioned by age, extension access, extension visits, awareness and farm size. Also, adoption had a significant positive impact on cassava yields. Adopters had 18 t/ha increases in yields and non-adopters should they have adopted had increases of 10 t/ha. Strategies to resource research extension linkage system to promote and create awareness about the existing improved cassava varieties for increased adoption are recommended. [ABSTRACT FROM AUTHOR]

The world faces a high alert of coronavirus disease 2019 (COVID-19), leading to a million deaths and could become infected to reach a billion numbers. A sizeable amount of scholarly work has been available on different aspects of social-economic and environmental factors. At the same time, many of these studies found the linear (direct) causation between the stated factors. In many cases, the direct relationship is not apparent. The world is unsure about the possible determining factors of the COVID-19 pandemic, which need to be known through conducting nonlinearity (indirect) relationships, which caused the pandemic crisis. The study examined the nonlinear relationship between COVID-19 cases and carbon damages, managing financial development, renewable energy consumption, and innovative capability in a cross section of 65 countries. The results show that inbound foreign direct investment first increases and later decreases because of the increasing coronavirus cases. Further, the rise and fall in the research and development expenditures and population density exhibits increasing coronavirus cases across countries. The continued economic growth initial decreases later increase by adopting standardized operating procedures to contain coronavirus disease. The inter-temporal relationship shows that green energy source and carbon damages would likely influence the coronavirus cases with a variance of 17.127% and 5.440%, respectively, over a time horizon. The policymakers should be carefully designing sustainable healthcare policies, as the cost of carbon emissions leads to severe healthcare issues, which are likely to get exposed to contagious diseases, including COVID-19. The sustainable policy instruments, including renewable fuels in industrial production, advancement in cleaner production technologies, the imposition of carbon taxes on dirty production, and environmental certifications, are a few possible remedies that achieve healthcare sustainability agenda globally. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread to more than 200 countries with a current case fatality ratio (CFR) of more than 2% globally. The concentration of air pollutants is considered a critical factor responsible for transmitting coronavirus disease among the masses. The photochemical process and coal combustions create respiratory disorders that lead to coronavirus disease. Based on the crucial fact, the study evaluated the impact of nitrous oxide (N2O) emissions, coal combustion, and traffic emissions on COVID-19 cases in a panel of 39 most affected countries of the world. These three air pollution factors are considered to form a lethal smog that negatively affects the patient's respiratory system, leading to increased susceptibility to coronavirus worldwide. The study used the Markov two-step switching regime regression model for obtaining parameter estimates. In contrast, an innovation accounting matrix is used to assess smog factors' intensity on possibly increasing coronavirus cases over time. The results show that N2O emissions, coal combustion, and traffic emissions increase COVID-19 cases in regime-1. On the other hand, N2O emissions significantly increase coronavirus cases in regime-2. The innovation accounting matrix shows that N2O emissions would likely have a more significant share of increasing coronavirus cases with a variance of 33.902%, followed by coal combustion (i.e., 6.643%) and traffic emissions (i.e., 2.008%) over the time horizon. The study concludes that air quality levels should be maintained through stringent environmental policies, such as carbon pricing, sustainable urban planning, green technology advancement, renewable fuels, and pollution less accessible vehicles. All these measures would likely decrease coronavirus cases worldwide. [ABSTRACT FROM AUTHOR]

This paper analyses the effects of gender and institutional support services on commercialisation patterns of maize by female-headed households (FHHs) and male-headed households (MHHs) in Western Kenya. Using primary household survey data from 297 maize farmers, we estimate a Tobit model and a treatment effect model to assess the determinants and gender-induced differences in commercialisation patterns, respectively. Results show that commercialisation levels of FHHs and MHHs were significantly and variably affected by institutional support services. The exogenous switching treatment effect model showed that the commercialisation intensity gap between MHHs and FHHs is explained by both observable and unobservable characteristics. [ABSTRACT FROM AUTHOR]

This paper presents a robust method for dealing with switching regression problems. Regression models with switch-points are broadly employed in diverse areas. Many traditional methods for switching regressions can falter in the presence of outliers or heavy-tailed distributions because of the modeling assumptions of Gaussian errors. The outlier corruption of datasets is often unavoidable. When misapplied, the Gaussian assumption can lead to incorrect inference making. The Laplace distribution is known as a longer-tailed alternative to the normal distributions and connected with the robust least absolute deviation regression criterion. We propose a robust switching regression model of Laplace distributed errors. To advance robustness, we extend the Laplace switching model to a fuzzy class model and create a robust algorithm named FCL through the fuzzy classification maximum likelihood procedure. The robustness properties and the advance of resistance against high-leverage outliers are discussed. Simulations and sensitivity analyses illustrate the effectiveness and superiority of the proposed algorithm. The experimental results indicate that FCL is much more robust than the EM-based algorithm. Furthermore, the Laplace-based algorithm is more time-saving than the t-based procedure. Diverse real-world applications demonstrate the practicality of the proposed approach.

Credit constraints come in various forms, to the extent that they translate ex ante into market entry barriers (mostly transaction cost, price, and risk constraints) or ex post into credit application rejection (quantity constraints). This article is concerned with the underlying generating mechanisms of such heterogeneity in credit constraints and the implications for farmers' productivity in the Senegal River Valley. Results from an endogenous switching regression model based on farm-level data indeed indicate that both pre- and postapplication constraints are holding back farmers' performance, with differential impact depending on whether the latter is based on the average treatment on the credit beneficiaries or on the nonbeneficiaries and on the productivity measure. This is in addition to significant differences in the generating factors of market entry barriers and credit application outcome. These results are suggestive of various policy options that would not only increase market participation and bring about its beneficial impact, but also contribute to improve smallholder farmers' credit-worthiness. [ABSTRACT FROM AUTHOR]

This paper proposes a new way of testing the effect of labor market reforms in the employment adjustment at the macro level. Following the approach to hysteresis based on the presence of non-convex costs of adjustment, a switching aggregate employment equation is estimated, with an unknown splitting factor, from a computational implementation of the linear play hysteresis operator. The play hysteresis operator describes a dynamics where non-convex adjustment costs create intervals of weak reaction of employment to small variations in forcing variables, while spurts in employment adjustment may occur as a consequence of a large, or cumulative small shocks. The main contribution of this paper is to extend an existing approach for the case where there are disruptive breaks, by accommodating changes in the value of the switching parameter of the employment equation whenever labor market reforms are present. Numerical experiments on the Portuguese economy are performed. [ABSTRACT FROM AUTHOR]

Stochastic plateau production functions provide improved fertilizer recommendations based on multi-year agronomic experiments where weather and other stochastic variables change over time. This research assesses the profitability of no-tillage corn production in northeastern Colorado and determines economically optimal nitrogen fertilizer rates. It also proposes an alternative parameterization of the linear response stochastic plateau model which provides a robustness check against traditional parameterizations. Results show the current use of nitrogen fertilizer in the area exceeds estimated economically optimal levels. This suggests that a reduction in nitrogen use could increase expected profits and simultaneously reduce environmental costs. [ABSTRACT FROM AUTHOR]

We examine the importance of financial constraints for firm investment by looking at the relationship between investment expenditures and proceeds from voluntary asset sales. Asset sales provide a cleaner indicator of liquidity than cash flows since it appears not to be positively correlated with investment opportunities. The cross-sectional differences in firm investment are examined using an endogenous switching regression model with unknown sample separation. We find that cash obtained from asset sales is a significant determinant of corporate investment and that the sensitivity of investment to proceeds from asset sales is significantly stronger for firms that are likely to be financially constrained. [ABSTRACT FROM AUTHOR]

This study presents an efficient version of test for the hypothesis that education plays a key role in influencing agricultural productivity based on a switching regression model. In the present setting, farmers’ ability to deal with disequilibria is allowed to change with education, which thereby provides a concrete evidence of the effect of education on selected East Asian production agriculture. The results suggest that there exists a threshold for education to be influential to agricultural productivity change when the selected East-Asian economies are categoried by their degree of economic development. Moreover, for the group of economies where education constitutes a major determinant of productivity growth in both the technological progression and/or stagnation/recession regimes, the effect of education is found to vary from economy to economy and from regime to regime. Generally speaking, however, those East-Asian economies tend to reach their turning point in short time despite of the mentioned differences. This result therefore leads to important policy implications concerning giving an impetus to human capital investment in the agriculture sector.

Highlights • China is the world largest producer and consumer of rice. • Assess the impact of adoption of DSR on rice yield and net rice income. • Using plot-level data from four provinces in southern China. • Plot level data shows yield increase by 3.1% for DSR adopters. • Net rice income increases by 66% if PTR method plots switched to DSR method. Abstract China is the world largest producer and consumer of rice. With stagnant yields, resource depletion, labor shortages direct-seed rice (DSR) is gaining the interest of rice producers in southern China. This study investigates the impact of the adoption of DSR on rice yield and net rice income of Chinese farmers. We use plot-level data from four provinces in southern China. Results indicate that rice yield increase by 3.1% for DSR adopters and by 0.7% if puddled transplanted rice (PTR) producers adopted DSR method. Finally, we find that net rice income increased by 66% if PTR method plots switched to DSR method. Adoption of DSR should be encouraged by policymakers. [ABSTRACT FROM AUTHOR]

Agriculture remains the mainstay of the Ethiopian economy. However, the sector is affected by climate change induced extreme weather events that aggravates rural poverty. As a result, the Ethiopian government has been making different interventions to alleviate poverty. Koga irrigation development project (KIDP) is one of such initiatives. However, due to political unrest, poor water management practice, limited market linkages and other institutional challenges, the project has not reached its desired goals. This paper is thus intended to evaluate the efficacy of the KIDP to reduce poverty. Data were collected from 395 sample farm households (220 irrigators and 175 non-irrigators) drawn using multi-stage sampling technique. Multidimensional poverty index and endogenous switching regression model were employed to measure poverty and estimate the impact of irrigation on household poverty, respectively. The study found that poverty intensity and multidimensional poverty index of the study area were lower than the national and regional averages. Nonetheless, the trend of poverty reduction was not evenly progressed in irrigator and non-irrigator households. The proportion of non-irrigator poor and MPI poor households were greater than irrigators. The endogenous switching model and key informant interviews proved that irrigation has positive impact on multidimensional household poverty reduction. However, the incidence of poverty among the sample households, regardless of access to irrigation, is still higher. This implies access to irrigation should be accompanied by institutional supports and complementary production inputs. So as to excel the impact of irrigation, the government shall also expand the technology over non-irrigated areas. [ABSTRACT FROM AUTHOR]

Credit unions differ in the types of financial services they offer to their members. This article explicitly models this observed heterogeneity using a generalized model of endogenous ordered switching. Our approach captures the endogenous choice that credit unions make when adding new products to their financial services mix. The model that we consider also allows for the dependence between unobserved effects and regressors in both the selection and outcome equations and can accommodate the presence of predetermined covariates in the model. We use this model to estimate returns to scale for U.S. retail credit unions from 1996 to 2011. We document strong evidence of persistent technological heterogeneity among credit unions offering different financial service mixes, which, if ignored, can produce quite misleading results. Employing our model, we find that credit unions of all types exhibit substantial economies of scale. [ABSTRACT FROM AUTHOR]

Understanding whether high healthcare costs for individuals persist over time is critical for the development of policies that aim to reduce the prevalence of high cost patients. And while high healthcare costs will occur in any given year based on the prevalence of certain morbidities and acute conditions, a large random component of the distribution means that it is rarely the same people driving the bulk of healthcare expenditures. Using administrative data for over 250,000 Australian residents for the years between 2006 and 2011, we analyse the persistence of high annual healthcare costs. We examine the prevalence of high cost persistence in this sample, and then, we use endogenous switching models to identify the morbidity groups that are related with high cost persistence. These models also measure cases of cost amplification that are associated with a history of high cost healthcare. This analysis uses data from multiple categories of healthcare, specifically medical services, pharmaceuticals and admitted patient care. While there is a relatively low number of patients with persistent high cost (approximately 3% of the sample), this group accounted for 19% of aggregate expenditure. Pharmaceuticals were the most persistently high cost category of healthcare with 5% of the sample accounting for 32% of aggregate pharmaceutical expenditure. The morbidities associated with notable cost amplifications are morbidities that are hard to prevent or involve escalations of adverse health states that are difficult to avert. This casts doubt on whether broad policies can reduce the prevalence of individuals with persistently high healthcare costs. [ABSTRACT FROM AUTHOR]

The aim of this paper is to evaluate and analyze the impact of adoption of soil conservation practices (SCPs) on the technical efficiency of smallholder rice producers in Central China. We address self-selection bias and unobserved heterogeneity problems by estimating a switching regression model for the adoption decision function and separate stochastic production frontiers for SCP and Conventional farms while allowing for production inefficiency. SCP farms exhibit statistically higher average technical efficiency than Conventional farms. Education, extension services, membership in cooperatives, access to credit, and alternative income sources are positively and significantly associated with technical efficiency for both groups. Conventional farms display higher partial output elasticity for land, while only SCP farms show significant elasticity for capital. [ABSTRACT FROM AUTHOR]

Abstract: In this study, we estimate the public sector wage premium in a post‐transition economy, a quarter of a century since the collapse of the old regime. Our methodology uses a copula method to estimate the switching regression model, which allows for the relaxation of the restrictive assumption of joint normality. We control for employment selection into both sectors using an instrument based on information regarding learned professions. We use data from the Polish Survey of Earnings by Occupations (2012). Contrary to earlier results for Poland, we found positive selection into employment in both sectors, with positive average treatment effect on the treated and negative average treatment effect on the untreated. The results suggest that both private and public sector employees select themselves into the sector in which they earn more than they would in a counterfactual scenario. [ABSTRACT FROM AUTHOR]

This paper considers the relationship between financial frictions and investment. In an effort to clarify the role of cash flow in examining the impact of capital market imperfections, endogenous switching regression models are estimated for a panel of 1122 UK firms listed on the London Stock Exchange over the period of 1981-2009. Not only is the financial regime which the firm faces endogenous, we also allow the regime to change over time via modeling efficiency using stochastic frontier analysis. The results reveal that a firm's constrained credit status changes with the improvement of its efficiency. Furthermore, the analysis reveals that financially constrained firm's investment is comparatively more sensitive to its cash flow. Moreover, this sensitivity is statistically significant and is negatively related with corporate efficiency. [ABSTRACT FROM AUTHOR]

The direct-seeded rice (DSR) establishment method can improve productivity and labor efficiency while taking into account the soil and hydrologic conditions of the field, the availability of appropriate land equipment, and irrigation-drainage systems. Using plot- and household-level data, we analyze the impacts of DSR adoption in two rice-growing states of India. We account for observed and unobserved heterogeneity using endogenous switching regression. We analyze the yield and costs effects of DSR adoption. Our study shows a small but significant effect of DSR adoption on yield and costs. We find increase in rice yields (by 3.74%) for DSR adopters; an increase in rice yields (by 6.79%) if the DSR method were adopted on puddled transplant rice (PTR) parcels. We find a 7.51% reduction in total costs for DSR adopters; a decrease in total costs (by 3.71%) if the DSR method was adopted on PTR parcels. DSR farmers can significantly reduce their fertilizer and land preparation costs. Hence, the decision to adopt DSR may help households with limited resources to reduce their cost of production without compromising the yield. [ABSTRACT FROM AUTHOR]