Solving endogeneity problems in multilevel estimation: an example using education production functions

Hanchane, Saïd; Mostafa, Tarek

doi:10.1080/02664763.2011.638705

Cited by 37 publications

(35 citation statements)

References 21 publications

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“…Moreover, this technique allows us to identify how much variance can be explained by each one of the three hierarchical levels, as we will see in the next section. Also, since all the variables are endogenous, the multilevel model with random intercepts allows each MFI and each region to have its own intercept that controls endogeneity at the MFI and region levels, as Hanchane and Mostafa () noted.…”

Section: Methodsmentioning

confidence: 99%

“…The second approach used was a multilevel model allowing for random intercepts, in which we break the variance and the error term. This multilevel approach can lead to more truthful and less biased conclusions (Hanchane & Mostafa, ). The third approach uses a propensity score matching in order to weigh the regression with the probability of being a smaller or a larger MFI.…”

Section: Conclusion Contributions and Policy Implicationsmentioning

confidence: 99%

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To profit or not to profit? Assessing financial sustainability outcomes of microfinance institutions

2019

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We used a multilevel approach on comparing for‐profit and not‐for‐profit microfinance institutions (MFIs). The database was composed of 202 MFIs (in 52 countries) from the most widely used microfinance dataset (the Microfnance Information eXchange, Inc. Market), with 669 observations from 2010 to 2014. Four financial sustainability outcomes were considered: yield on gross portfolio; return on assets; portfolio at risk, 30 days; and operational self‐sufficiency (OSS). Although for‐profit MFIs had a higher Yield, there was no significant effect of profit orientation on ROA, PAR30, and OSS. Further analysis shows that although profit orientation has a significant effect on the yield of small MFIs, it does not have any effect on larger MFIs, which is consistent with the theory that larger MFIs can distribute its fixed costs better, requiring lower interest rates and allowing smaller yield on the gross portfolio. In addition, we show that the intrinsic characteristics of the MFIs account for the majority of the variance from the four outcomes.

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Section: Methodsmentioning

confidence: 99%

Section: Conclusion Contributions and Policy Implicationsmentioning

confidence: 99%

To profit or not to profit? Assessing financial sustainability outcomes of microfinance institutions

2019

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“…If there is a significant difference (and not just that the between effect is significant different from zero) the terms should not be combined, and the encompassing within-between or Mundlak model should be used. This was done by Hanchane and Mostafa (2012) considering bias with this model for school (level 2) and student (level 1) performance. They found that in less selective school systems (Finland), there was little bias and a model like Eq.…”

Section: Random Effects Without Within and Between Separationmentioning

confidence: 99%

Fixed and random effects models: making an informed choice

2018

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This paper assesses the options available to researchers analysing multilevel (including longitudinal) data, with the aim of supporting good methodological decision-making. Given the confusion in the literature about the key properties of fixed and random effects (FE and RE) models, we present these models' capabilities and limitations. We also discuss the within-between RE model, sometimes misleadingly labelled a 'hybrid' model, showing that it is the most general of the three, with all the strengths of the other two. As such, and because it allows for important extensions-notably random slopes-we argue it should be used (as a starting point at least) in all multilevel analyses. We develop the argument through simulations, evaluating how these models cope with some likely mis-specifications. These simulations reveal that (1) failing to include random slopes can generate anticonservative standard errors, and (2) assuming random intercepts are Normally distributed, when they are not, introduces only modest biases. These results strengthen the case for the use of, and need for, these models.

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“…As proven by Baltagi (), the Wald test on these additional slopes can be used to verify the assumption of exogeneity of individual MCB variables. As Mundlak () works well in a cross‐sectional framework (see e.g., Rabe‐Hesketh and Skrondal ; Snijders and Berkhof ; Grilli and Rampichini ; Hanchane and Mostafa ; Aiello and Ricotta ), we perform some MLM regressions by considering a 2‐level hierarchy with small banks at the first level and provinces at the second level. These auxiliary estimations are meant to be just a robustness check of the empirical evidence obtained when estimating the Equation .…”

Section: The Empirical Setting: Models and Datamentioning

confidence: 99%

Multilevel empirics for small banks in local markets

Aiello

Bonanno

2018

Papers in Regional Science

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Banking is increasingly a-spatial. However, the environment matters for small banks. Indeed, they are embedded in narrowed markets and hence benefit from proximity to their member-customers. By referring to multilevel approach, this article aims at measuring how much the performance of Italian mutual-cooperative banks is determined by both geographical (provincial level) and individual characteristics (small bank level). The effect of local markets explains 28.27% of bank heterogeneity in the empty multilevel model and 33% in the most extended model. Moreover, it is found that bank efficiency increases with market concentration and demand density and decreases with branching in local markets.JEL codes: G21, C13, D00, R19

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Solving endogeneity problems in multilevel estimation: an example using education production functions

Cited by 37 publications

References 21 publications

To profit or not to profit? Assessing financial sustainability outcomes of microfinance institutions

To profit or not to profit? Assessing financial sustainability outcomes of microfinance institutions

Fixed and random effects models: making an informed choice

Multilevel empirics for small banks in local markets

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