scholarly journals Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects

2020 ◽  
Author(s):  
Jiti Gao ◽  
Fei Liu ◽  
Bin Peng
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Binary Response ◽  
Response Models ◽  
Interactive Fixed Effects ◽  
Binary Response Models ◽  
Heterogeneous Panel

scholarly journals Modeling of Credit Institution License Withdrawal Based on Panel Data

2018 ◽  
Vol 3 (2) ◽  
pp. 309
Author(s):  
Domashova D.V. ◽  
Kripak Е.М. ◽  
Pisarchik Е.Е. ◽  
Ulanova Zh.U.
Keyword(s):  
Panel Data ◽  
Financial Performance ◽  
General Model ◽  
Binary Response ◽  
Credit Institution ◽  
Response Models ◽  
Probit Models ◽  
Source Data ◽  
Logit And Probit Models ◽  
Binary Response Models

The research paper involves the construction of panel data binary response models to forecast the probability of a credit institution's license withdrawal based on its financial performance, including the construction of logit and probit models using various sets of source data offers a technique for shaping a general model. Keywords: credit institutions, panel data, binary response models, license withdrawal

scholarly journals TESTING HOMOGENEITY IN PANEL DATA MODELS WITH INTERACTIVE FIXED EFFECTS

2013 ◽  
Vol 29 (6) ◽  
pp. 1079-1135 ◽  
Author(s):  
Liangjun Su ◽  
Qihui Chen
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Data Models ◽  
Development Economic ◽  
Strong Mixing ◽  
Panel Data Models ◽  
Finite Sample ◽  
Test Statistic ◽  
Lm Test ◽  
Interactive Fixed Effects

This paper proposes a residual-based Lagrange Multiplier (LM) test for slope homogeneity in large-dimensional panel data models with interactive fixed effects. We first run the panel regression under the null to obtain the restricted residuals and then use them to construct our LM test statistic. We show that after being appropriately centered and scaled, our test statistic is asymptotically normally distributed under the null and a sequence of Pitman local alternatives. The asymptotic distributional theories are established under fairly general conditions that allow for both lagged dependent variables and conditional heteroskedasticity of unknown form by relying on the concept of conditional strong mixing. To improve the finite-sample performance of the test, we also propose a bootstrap procedure to obtain the bootstrap p-values and justify its validity. Monte Carlo simulations suggest that the test has correct size and satisfactory power. We apply our test to study the Organization for Economic Cooperation and Development economic growth model.

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