Maximum Likelihood Estimation of Endogenous Switching Regression Models

By Michael Lokshin, Z. Sajaia. 2004

957 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/2c6a188b1e5342836b0e8496bae3b692ede9b6d9

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Citations in the corpus

Does cooperative membership improve household welfare? Evidence from a panel data analysis of smallholder dairy farmers in Bihar, India (2018, methodology): “This study uses an endogenous switching regression approach to account for sample selection bias (Lokshin and Sajaia, 2004).”
Copula-Based Maximum-Likelihood Estimation of Sample-Selection Models (2013, methodology): “The Stata commands heckman and movestay (Lokshin and Sajaia 2004) implement the maximum likelihood estimation of the bivariate sample-selection model and the endogenous switching regression model, respectively, under the assumption of joint normality.”
Poverty Reduction Effects of Agricultural Technology Adoption: A Micro-evidence from Rural Tanzania (2012, methodology): “An efficient method to estimate endogenous switching regression models is by full information maximum likelihood (FIML) estimation (Lee and Trost, 1978; Lokshin and Sajaia, 2004; Di Falco et al., 2011).”
Impacts of extension access and cooperative membership on technology adoption and household welfare (2017, methodology): “We, therefore, employed an ESRmodel that accounts for both observed and unobserved sources of bias (Lokshin and Sajaia, 2004; Shiferaw et al., 2014; Ma and Abdulai, 2016).”
Crop productivity and adaptation to climate change in Pakistan (2018, background): “This is indicative of the presence of positive unobserved selection bias in the adaptation decision (Lokshin and Sajaia, 2004).”
Yield Effects of Tissue Culture Bananas in Kenya: Accounting for Selection Bias and the Role of Complementary Inputs (2012, methodology): “A more efficient and consistent way to estimate the ESR model is the full information maximum likelihood (FIML) method (Greene, 2003; Lokshin and Sajaia, 2004).”
Impact of modern agricultural technologies on smallholder welfare: Evidence from Tanzania and Ethiopia (2012, methodology): “The FIML estimates of the parameters of the endogenous switching regression model can be obtained using the movestay command in STATA (Lokshin and Sajaia, 2004).”
Credit Constraints and Agricultural Productivity: Evidence from rural Rwanda (2014, positive): “…studies estimate each equation separately (Carter, 1989; Feder et al., 1990; Carter and Olinto, 2003; Petrick, 2004; Guirkinger and Boucher, 2008), the FIML method estimates both selection and outcome equations simultaneously, generating consistent standard errors (Lokshin and Sajaia, 2004).”