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  • Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models x
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Miyoko Asai
,
Qiaoe Chen
,
Mr. Jiro Honda
,
Xingwei Hu
, and
Qianqian Zhang
This paper examines the role of structural fiscal policies to promote female labor force participation and reduce gender gaps in labor markets in 26 OECD countries from 2000 to 2019. As both female labor force participation and many explanatory/control variables clearly exhibit non-stationarity (potentially leading to spurious regression results), we employ a panel vector error-correction model, in contrast with most previous empirical studies on this matter. Our analyses confirm statistically significant positive impacts of government spending on (1) early childcare and education, (2) active labor market programs, and (3) unemployment benefits, all of which would help encourage women to enter the labor force, while (4) an increase in relative tax rate on second earner could have negative impact on female labor force participation.
Brandon Buell
,
Reda Cherif
,
Carissa Chen
,
Jiawen Tang
, and
Nils Wendt
The COVID-19 pandemic underscores the critical need for detailed, timely information on its evolving economic impacts, particularly for Sub-Saharan Africa (SSA) where data availability and lack of generalizable nowcasting methodologies limit efforts for coordinated policy responses. This paper presents a suite of high frequency and granular country-level indicator tools that can be used to nowcast GDP and track changes in economic activity for countries in SSA. We make two main contributions: (1) demonstration of the predictive power of alternative data variables such as Google search trends and mobile payments, and (2) implementation of two types of modelling methodologies, machine learning and parametric factor models, that have flexibility to incorporate mixed-frequency data variables. We present nowcast results for 2019Q4 and 2020Q1 GDP for Kenya, Nigeria, South Africa, Uganda, and Ghana, and argue that our factor model methodology can be generalized to nowcast and forecast GDP for other SSA countries with limited data availability and shorter timeframes.
Ms. Grace B Li
,
Mr. Stephen A. O'Connell
,
Mr. Christopher S Adam
,
Mr. Andrew Berg
, and
Mr. Peter J Montiel
VAR methods suggest that the monetary transmission mechanism may be weak and unreliable in low-income countries (LICs). But are structural VARs identified via short-run restrictions capable of detecting a transmission mechanism when one exists, under research conditions typical of these countries? Using small DSGEs as data-generating processes, we assess the impact on VAR-based inference of short data samples, measurement error, high-frequency supply shocks, and other features of the LIC environment. The impact of these features on finite-sample bias appears to be relatively modest when identification is valid—a strong caveat, especially in LICs. However, many of these features undermine the precision of estimated impulse responses to monetary policy shocks, and cumulatively they suggest that “insignificant” results can be expected even when the underlying transmission mechanism is strong.