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Uses Bank of Italy’s Survey on Household Income and Wealth (SHIW) panel data for 1993 and 1995 to model transition probabilities at the bottom of the Italian wage distribution and to investigate the features and determinants of low‐wage mobility. The analysis is based on a bivariate probit model with endogenous switching which allows tackling the initial conditions problem, i.e. the potential endogeneity of the conditioning starting state. Results show the appropriateness of such a choice, the hypothesis of exogenous initial conditions being always rejected. Shows that while some factors such as education, sex and geographical location have an effect on low‐pay persistence, job‐related variables are more effective in avoiding falls into low pay from higher pay. It is also shown how raw persistence involves a considerable share of true state dependence, i.e. the experience of low pay raises, per se, the probability of future low‐pay episodes, irrespective of personal attributes.

The purpose of this paper is to examine the impact of agricultural cooperative membership on farmers’ decisions to adopt integrated pest management (IPM) technology and to estimate the impact of IPM adoption on farm economic performance.

An endogenous switching probit model that addresses the sample selection bias issue arising from both observed and unobserved factors is used to estimate the survey data from a sample of 481 apple households in China. A treatment effects model is employed to estimate the impact of IPM adoption on apple yields, net returns and agricultural income. In order to address the potential endogeneity associated with off-farm work variable in estimating both cooperative membership choice specification and IPM adoption specifications, a control function approach is used.

The empirical results show that cooperative membership exerts a positive and significant impact on the adoption of IPM technology. In particular, farmers’ IPM adoption decision is significantly associated with household and farm-level characteristics (e.g. education, farm size and price knowledge). IPM adoption has a positive and statistically significant impact on apple yields, net returns and agricultural income.

The findings indicate that agricultural cooperatives can be a transmission route in the efforts to proliferate the adoption and diffusion of IPM technology, and increased IPM adoption tends to improve the economic performance of farm households.

Despite the widespread evidence of health and environmental benefits associated with IPM technology, the adoption rate of this technology remains significantly low. This paper provides a first attempt by investigating to what extent and how agricultural cooperative membership affects IPM adoption and how IPM adoption influences farm economic performance.

The purpose of this study is to estimate the profitability of rice production for irrigated and rain-fed farmers; determine the factors that influence farmers' decision to participate in irrigation and the impact of irrigation on rice farmers' profitability in northern Ghana.

Using cross-sectional data collected from 543 rice farmers in northern Ghana, the study employed both non-parametric (cost benefit analysis) and parametric (endogenous switching regression) approaches to analyse the data.

The empirical results reveal a significant difference between the profits of irrigated (GHS 2442.30) and rain-fed farmers (GHS 576.20), as well as the cost-benefit ratios between irrigators (2.53) and rain-fed farmers (1.37). Also, participation in irrigation was found to be influenced by relatively small farm size and off-farm income; while profitability was influenced by membership in a farmer-based organization, access to agricultural extension services and perception of decreasing rainfall intensity. Irrigation also had a positive significant net impact on profitability of rice production.

The results provide justification for development partners and the government of Ghana through the “one-village-one-dam” policy, to invest in irrigation in northern Ghana in order to improve household welfare as well as build resilience for sustainable production systems.

This study is the first of its kind to provide a robust analysis of the difference in profits of rain-fed and irrigated rice farmers while estimating the determinants of Ghanaian farmers' choice of either of the regimes within a bias-corrected framework.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

The paper examines the effect of internal remittances on the employment choices of household heads in rural Ghana.

The paper employs data from the Ghana Living Standards Survey (GLSS 6) of the Ghana Statistical Service. Due to issues of endogeneity of remittances in relation to labor supply, the paper adopts an instrumental variable approach in the analysis. First, employment choices are categorized into three: (1) wage/salary employment, (2) self-employment and (3) domestic/family employment. The relationship is then modeled as instrumental variable multinomial probit (IV-MNP). Secondly, employment choices are recategorized into two: farm employment and otherwise and modeled as instrumental variable probit (IV-PROBIT). The models are estimated via the conditional mixed process (CMP) estimation technique.

The results indicate that remittances have a negative effect on self-employment and a positive effect on domestic/family employment. Thus, remittances reduce participation in self-employment but increase participation in domestic/family employment. Furthermore, remittances have a negative effect on participation in farm employment. The results are robust to different measures of remittances: receipt of remittances (dummy) and remittance income.

The results suggest that remittances are used for consumption rather than investing in earning activities. In general, engaging in earning type of employment, whether farm and nonfarm employment will decline with receipt of remittances in rural Ghana. There is a need for policy attention with the increasing migration of people out of rural areas.

Prior to this study, little was known on the effect of internal remittances on labor supply decisions of remittance recipients in Ghana, particularly rural Ghana. This paper contributes significantly to filling this knowledge gap.

We discuss a class of copula-based ordered probit models with endogenous switching. Such models can be useful for the analysis of self-selection in subjective well-being equations in general, and job satisfaction in particular, where assignment of regressors may be endogenous rather than random, resulting from individual maximization of well-being. In an application to public and private sector job satisfaction, and using data on male workers from the German Socio-Economic Panel for 2004, and using two alternative copula functions for dependence, we find consistent evidence for endogenous sector selection.

The purpose of this paper is to determine if there are positive microeconomic effects from a state‐funded loan participation program on farm productivity and investment behavior.

The authors take the approach that access to credit solves a liquidity problem. If a credit constraint exists it results in a suboptimal allocation of resources and a reduction in farm output and profitability. A two‐stage regression model approach is used to analyze farmer survey and loan application data. In the first stage, a probit regression model is used to identify the farmers who are likely to be credit rationed. In the second stage, switching regression models are used to observe the effect of credit rationing on farm productivity and on farm investment behavior.

It is found that there are liquidity effects of credit constraints for a significant share of the beginning and low‐resource farmers who participated in the state‐funded farm loan program. After controlling for various farm and farmer characteristics, the estimated productivity and investment demand equations imply that a 1 percent increase in credit received by credit constrained farmers under the state program increased their gross income by about 0.49 percent, and their investments in depreciable assets by about 0.33 percent.

This paper is the first to apply the switching regression model to a state‐funded farm loan program for the purpose of evaluating the financial impacts on farmer participants.

I propose a general framework for instrumental variables estimation of the average treatment effect in the correlated random coefficient model, focusing on the case where the treatment variable has some discreteness. The approach involves adding a particular function of the exogenous variables to a linear model containing interactions in observables, and then using instrumental variables for the endogenous explanatory variable. I show how the general approach applies to binary and Tobit treatment variables, including the case of multiple treatments.

This chapter deals with the estimation of the effect of exchange rate flexibility on financial account openness. The purpose of our analysis is twofold: On the one hand, we try to quantify the differences in the estimated parameters when exchange rate flexibility is treated as an exogenous regressor. On the other hand, we try to identify how two different degrees of exchange rate flexibility (intermediate vs floating regimes) affect the propensity of opening the financial account. We argue that a simultaneous determination of exchange rate and financial account policies must be acknowledged in order to obtain reliable estimates of their interaction and determinants. Using a panel data set of advanced countries and emerging markets, a trivariate probit model is estimated via a maximum simulated likelihood approach. In line with the monetary policy trilemma, our results show that countries switching from an intermediate regime to a floating arrangement are more likely to remove capital controls. In addition, the estimated coefficients exhibit important differences when exchange rate flexibility is treated as an exogenous regressor relative to the case when it is treated as endogenous.

Both issuing firms and underwriters shall benefit from the associations in underwriting contracts for seasoned equity offerings (SEOs). Issuing firms that are offered underwriting contracts with clustered gross spreads do not have strong incentives to switch away from the firms' prior SEO underwriters, and thus these existing underwriters are able to maintain or gain greater market share. This study investigates how the clustering of percentage gross spreads affects the likelihood of underwriter switching.

Using the investment bank-underwritten SEOs in Hong Kong, the authors find that the percentage gross spreads of 40% of these SEOs are clustered at 2.5%. The seemingly unrelated bivariate probit model, Weibull survival mixed model and trivariate probit model are applied to analyse this phenomenon.

The authors' study provides first direct evidence that the clustering of percentage gross spreads lowers the likelihood of underwriter switching. Investment banks as underwriters can explicitly price underwriting contracts at a clustered level, more likely in periods of greater market volatility, and intentionally retain the banks' client firms using pricing arrangements. The authors' finding and approach offer more direct and distinct support that the issuer–underwriter association can be relationship-based.

Whilst the clustering of fees is interpreted as a type of anticompetitive price sitting, the authors contribute to literature by providing new empirical evidence on why percentage gross spreads as a price dimension are clustered. On top of contract efficiency and collusion, this study's new evidence provides a third view for the clustering of gross spreads.