Recognising that aid effectiveness critically depends upon the quality of host country institutions and policies, international aid agencies have sought to inform their activities through more systematic political economy analysis (PEA). Three analytical frameworks for PEA are compared,...

This paper examines the tensions that exist in financial inclusion policy between donor approaches founded on market modernism and governments with more activist leanings. It draws on political economy analysis - now frequently used by donors themselves - to demonstrate the underlying dynamics...

Incluye bibliografía ; El estimador de Arellano y Bond (1991) es muy popular entre los investigadores empíricos para estimar modelos dinámicos de panel con efectos fijos y regresores endógenos. Sin embargo, dicho estimador puede presentar sesgos cuando el número de unidades del panel (N) es...

In this talk, we will show how to use simulations in Stata to explore to what extent and under what circumstances a test is problematic. We will illustrate this for a set of tests of the parallel regression assumption in ordered logit and probit models: the Brant, likelihood ratio, Wald, score,...

Low national saving, a persistent current account deficit and the rapid expansion of balance sheets are potential reasons why the UK economy needs to rebalance. Global factors are likely to have been an important driver of these developments, but domestic factors have played an important role in...

Top-down stress testing is one way of assessing the resilience of the financial system to the risks it might face now or in the future. The Risk Assessment Model of Systemic Institutions (RAMSI) developed at the Bank of England is an example of a top-down stress-testing model and is part of the...

This article reviews Regression Models for Categorical Dependent Variables Using Stata, Second Edition, by Long and Freese.

-gologit2- is a user-written program that estimates generalized logistic regression models for ordinal dependent variables. The actual values taken on by the dependent variable are irrelevant except that larger values are assumed to correspond to "higher" outcomes. A major strength of -gologit2-...

The assumptions of the ordered logit/probit models estimated by ologit and oprobit are often violated. When an ordinal regression model incorrectly assumes that error variances are the same for all cases, the standard errors are wrong and (unlike OLS regression) the parameter estimates are...

When a binary or ordinal regression model incorrectly assumes that error variances are the same for all cases, the standard errors are wrong and (unlike OLS regression) the parameter estimates are biased. Heterogeneous choice/ location-scale models explicitly specify the determinants of...