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The purpose of this paper is to investigate how credit access affects the welfare of households and sheds light on how household characteristics influence the decision to take credit and the efficiency in credit use.

This study uses data from the fourth round of the Ethiopian Rural Household Survey conducted in 2009, and examines factors that determine the decision to take credit and the effect of such decision on household welfare. The household welfare variable is measured by the food security indicator and total food expenditure. The study employs endogenous Regime Switching model to account for endogeneity in access to credit and self-selection bias in the decision to participate in credit.

The result from the kernel distribution shows households with access to credit have more consumption expenditure than those without access to credit. The ordinary least square regression shows that access to credit increases total consumption by 12 percent without considering self-selection bias. Participation in non-farm activity increases the demand for credit by 17 percent. Land holding, household size, and participation in saving associations increase the probability of getting credit by 5, 11, and 20 percent, respectively. Access to credit appears to have a positive impact on food security in both actual and counterfactual cases for the current credit receivers.

This study provides a thorough analysis of the impacts of access to credit on household welfare in Ethiopia. The study contributes to the debate on the link between access to credit and household welfare and provides valuable input for policy makers.

The purpose of this study is to assess the impact of credit constraints on agricultural labour productivity as well as the impact of credit constraints and agricultural labour productivity on rural households' consumption in Ghana.

This study uses the Ghana Living Standard Survey round six (GLSS 6) as the main source of data, which happens to be one of the most comprehensive household datasets in Ghana. Quantitative estimation techniques (namely: Endogenous Switching Regression and Two Stage Least Squares) are used to address possible endogeneity and selection into credit markets.

First, large households are prone to credit constraints while age (experience) and compliance with extension advice reduce credit constraints. Second, the determinants of agricultural labour productivity for both constrained and unconstrained households are age, sex, farm equipment, herbicide and farm size. Third, household size, education and livestock rearing influence agricultural labour productivity of constrained households. Fourth, credit constraints, irrespective of how they are measured, impede agricultural labour productivity while access to credit fosters labour productivity. Lastly, credit constraints robustly reduce consumption while agricultural labour productivity strongly enhances rural households' consumption.

The first contribution is that, unlike most previous studies, we do not focus on the widely used measure of productivity – output per unit land, but on agriculture labour productivity in particular. Secondly, unlike most previous studies which examine the effect of credit constraints either on productivity alone or consumption alone, our study examines the impact of credit constraints on both. Thirdly, unlike the existing literature which uses one or two measures of credit constraints, we use a wide range of measures of credit constraints – seven different measures of credit constraints. Lastly, our empirical strategy solves at least two critical econometric problems – sample selection bias and endogeneity.

This study identified the determinants of improved rice variety adoption and measured their impact on farm productivity and the income of smallholder farmers in Indonesia.

We used a multistage sampling procedure and data from household surveys in four districts in the Banten region of Indonesia. An endogenous switching regression (ESR) model was used to estimate the impact of adoption, and the propensity score matching (PSM) non-parametric method tested the strength of the ESR findings.

The farm productivity of adoption increased by 11.45% and the income of smallholder farmers increased by 12.10% when compared to that of traditional methods.

The positive and significant effects of improved rice variety adoption indicated that research programs that develop improved rice varieties can optimize the productivity and income of smallholder farmers.

Adopting improved rice varieties increases the productivity and income of smallholder farmers, and the level of education, rice farming experience, access to extension workers, off-farm work, and mobile phone ownership have positive and significant effects on the adoption of improved rice varieties.

The purpose of the paper is to advocates the use of gendered economic policies to stimulate a post-COVID-19 recovery. It alerts on the risk of ignoring the female dimension of the current crisis and of resorting again to austerity programs that, like the ones enacted after the 2008 crisis, would hit women and mothers disproportionally harder than other groups.

The authors use data from the British Household Panel Survey on female participation and account for gendered constraints and enablers missed by mainstream economics. Using a sequential empirical approach, the authors simulate various welfare policy scenarios that address factors, such as childcare costs, personal and social nudges, that could help women back into the labor market in the aftermath of a crisis.

The authors found that incentive-type interventions, such as subsidies, promote female labor market participation more effectively than punishment-austerity type interventions, such as benefits' cuts. Policies oriented to alleviate childcare constraints can be sustainable and effective in encouraging women back to work. Considering factors wider than the standard economic variables when designing labor market policies may provide fruitful returns.

The sequential methodology enables to estimate current and counterfactual incomes for each female in the sample and to calculate their prospective financial gains and losses in changing their labor market status quo, from not employed into employed or vice-versa. Welfare policies affect these prospective gains and losses and, by interacting with other factors, such as education, number and age of children and social capital, prompt changes in women's labor market choices and decision.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

We compare the finite sample power of short- and long-horizon tests in nonlinear predictive regression models of regime switching between bull and bear markets, allowing for time varying transition probabilities. As a point of reference, we also provide a similar comparison in a linear predictive regression model without regime switching. Overall, our results do not support the contention of higher power in longer horizon tests in either the linear or nonlinear regime switching models. Nonetheless, it is possible that other plausible nonlinear models provide stronger justification for long-horizon tests.

The aim of this study was to determine if there are asymmetries in the pass-through of West Texas Intermediate (WTI) crude oil prices to its derivatives (diesel and gasoline) in the Brazilian market.

Initially, the future WTI oil price series was analyzed using the self-exciting threshold autoregressive (SETAR) and logistic smooth transition autoregressive (LSTAR) non-linear models. Subsequently, the threshold autoregressive error-correction model (TAR-ECM) and Markov-switching model were used.

The findings indicated high prices throughout 2008 due to the subprime crisis. The findings indicated high prices throughout 2008 due to the subprime crisis. The results indicated that there is long-term pass-through of oil prices in both methods, suggesting an equilibrium adjustment in the prices of diesel and gasoline in the analyzed period. Regarding the short term, the variations in contemporary crude oil prices have positive effects on the variations in fuel prices. Lastly, this behavior can partly be explained by the internal price management structure adopted during almost all of the analyzed period.

This paper contributes to the literature at some points. The first contribution is the modeling of the oil price series through non-linear models, further enriching the literature on the recent behavior of this time series. The second is the simultaneous use of the TAR-ECM and Markov-switching model to capture possible short- and long-term asymmetries in the pass-through of prices, as few studies have applied these methods to the future price of oil. The third and main contribution is the investigation of whether there are asymmetries in the transfer of oil prices to the price of derivatives in Brazil. So far, no work has investigated this issue, which is very relevant to the country.

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.

This paper aims to examine the response of monetary policy to financial instability in the West African Economic and Monetary Union.

Through annual aggregated data from 1970 to 2019, the empirical strategy is based on the Markov regime-switching model with fixed probabilities.

The results revealed that the monetary policy of the central bank of the West African Economic and Monetary Union is characterized by two regimes (calm and distress) with respect to the trend of financial stability. The authors also found that the occurrence of the calm regime was likely greater than that of the distress regime. In addition, the calm regime is longer than the distress regime. The authors finally revealed that the central bank reacts to financial instability risk by increasing its short-term interest rate when financial instability reaches a threshold.

The limitation of this study is the unavailability of monthly or quarterly data that are more suitable for the methodological approach adopted.

This study is the one to estimate the response of the Central Bank of West African Countries to financial stress using a novel approach based on the Markov-Switching regression.

The authors propose novel tests for the detection of Markov switching deviations from forecast rationality. Existing forecast rationality tests either focus on constant deviations from forecast rationality over the full sample or are constructed to detect smooth deviations based on non-parametric techniques. In contrast, the proposed tests are parametric and have an advantage in detecting abrupt departures from unbiasedness and efficiency, which the authors demonstrate with Monte Carlo simulations. Using the proposed tests, the authors investigate whether Blue Chip Financial Forecasts (BCFF) for the Federal Funds Rate (FFR) are unbiased. The tests find evidence of a state-dependent bias: forecasters tend to systematically overpredict interest rates during periods of monetary easing, while the forecasts are unbiased otherwise. The authors show that a similar state-dependent bias is also present in market-based forecasts of interest rates, but not in the forecasts of real GDP growth and GDP deflator-based inflation. The results emphasize the special role played by monetary policy in shaping interest rate expectations above and beyond macroeconomic fundamentals.