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De keuze van een monetair beleidsstrategie is een gewichtig onderwerp van onderzoek binnen de economische wetenschappen en de beleidsvorming van centrale banken. Vanwege het feit dat landen doorgaans niet vasthouden aan één bepaalde monetaire strategie, maar van tijd tot tijd veranderen, kan men zich afvragen wat de keus voor monetair beleidsstrategie beïnvloed en wat de mogelijke macro-economische gevolgen zijn van dergelijke keuzes. Dit proefschrift richt zich op de analyse van twee monetaire beleidsstrategieën die uitgevoerd worden door centrale banken, namelijk: monetary targeting en inflation targeting. In het proefschrift onderzoek ik welke macro-economische, fiscale, externe, financiële en institutionele factoren van invloed zijn in de besluitvorming om monetary targeting te verlaten of om inflation targeting te implementeren. Daarnaast wordt in dit werk een uitgebreide analyse gepresenteerd over de effecten van inflation targeting op inflatie.

This paper examines which economic, fiscal, external, financial, and institutional characteristics of countries affect the likelihood that they adopt inflation targeting (IT) as their monetary policy strategy. We estimate a panel binary response model for 60 countries and two subsamples consisting of Organization for Economic Cooperation and Development (OECD) and non‐OECD countries over the period 1985–2008. The findings suggest that past macroeconomic performance of a country, its fiscal discipline, exchange rate arrangements, as well as the structure and development of its financial system have a significant impact on the likelihood to adopt IT. However, the factors leading to IT adoption differ significantly between OECD and non‐OECD countries. (JEL E42, E52)

This paper examines how the analysis of inflation targeting (IT) adoption is affected by allowing for a structural change after adoption, using panel probit models for 60 countries over the period 1985-2008. Our findings suggest that there is a structural change after IT adoption. Including the post-adoption period when estimating the factors of IT adoption leads to biased results when interested in the question as of what drives countries' decision to adopt IT.

This paper adopts a spatial probit approach to explain interaction effects among cross-sectional units when the dependent variable takes the form of a binary response variable and transitions from state 0 to 1 occur at different moments in time. The model has two spatially lagged variables: one for units that are still in state 0 and one for units that had already transferred to state 1. The parameters are estimated on observations for those units that are still in state 0 at the start of the different time periods, whereas observations on units after they transferred to state 1 are discarded, just as in the literature on duration modeling. Furthermore, neighboring units that had not yet transferred may have a different impact from units that had already transferred. We illustrate our approach with an empirical study of the adoption of inflation targeting for a sample of 58 countries over the period 1985-2008. Copyright (C) 2016 John Wiley & Sons, Ltd.

IntroductionGlobal HIV‐1 prevalence is 35.3 million [1]; women comprise >50% of those infected. The majority of women may lack regular care and only one‐fourth are virologically suppressed [2]. ELLA is a cross‐sectional, non‐interventional study conducted across Europe, Latin America, Canada and Asia that describes barriers to care for HIV‐infected women and associations with disease stage, symptoms and health‐related quality of life (HRQoL).MethodsHIV‐infected women eligible for ELLA (≥18 years) completed: Barrier to Care Scale (BACS) comprising 12 items in four domains (Index range 0–12, Overall range 1–4, greater=more barriers, Overall score ≥2 considered severe); AIDS Clinical Trials Group (ACTG) Health Status Assessment comprising 21 items assessing 9 HRQoL domains (range 0–100, greater=better); and ACTG Symptom Distress Module comprising 20 symptoms rated on bother (range 0–4, greater=more bother). Healthcare providers documented medical history and HIV clinical data. Correlations of BACS response and last reported VL/CD4 count with HIV symptoms and HRQoL were analyzed. Spearman rank order was used to test correlations with statistical significance set at p<0.05.ResultsEnrollment: 1931 women from 30 countries; mean age 40 years (16.9% >50 years); 47.7% education <12 years; 36% unemployed; 82.9% urban residence. HIV was acquired heterosexually in 83.0%; 88.2% of subjects were on ART; 57.5% had VL<50 c/ml; mean CD4 was 540.5 c/µL. Mean [SD] BACS Index and Overall scores were 6.19 [3.47] (N=1818) and 2.09 [0.71] (N=1922), respectively. Stigma was a prominent barrier. Lower (better) BACS Index and Overall scores correlated with better HRQoL on all nine domains (p<0.0001). Lower VL and greater CD4 count were both correlated with better HRQoL for eight of nine domains (p<0.04, p≤0.0002, respectively) excepting pain. Lower BACS Index and Overall scores correlated with fewer symptom count and less symptom bother (p<0.0001). Fewer symptom count and less symptom bother correlated with better HRQoL on all nine domains (p<0.0001). While greater CD4 count correlated with fewer HIV symptoms and less bother (p<0.0001), VL did not significantly correlate with either.ConclusionsIn HIV‐infected women, reduced barriers to care correlated with fewer symptoms, less symptom bother and better HRQoL. Improved HRQoL may be mediated by greater CD4 counts and fewer symptoms. Better access to care may improve HRQoL outcomes in this population.