Okun’s Law across time and frequencies

Aguiar‐Conraria, Luís; Martins, Manuel M. F.; Soares, Maria Joana

doi:10.1016/j.jedc.2020.103897

Cited by 29 publications

(13 citation statements)

References 35 publications

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“…Another contribution of this paper is related to the assumption of elasticity homogeneity. In contrast to previous research by Tang and Bethencourt (2017); Novák and Darmo (2019); Aguiar-Conraria et al (2020); Christopoulos et al (2023); Kim et al (2020), we hypothesize (H2) that elasticity continuously changes throughout the same phase of the business cycle depending on the maturity of the business cycle phase. In this paper we introduce a specification that makes it possible to estimate conditional elasticity, when elasticity is heterogeneous over the same phase of the business cycle.…”

Section: Introductioncontrasting

confidence: 79%

When and for Whom Does Growth Becomes Jobless?

Butkus,

Dargenytė-Kacilevičienė,

Matuzevičiūtė

et al. 2024

Economies

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The results of previous research suggest that the elasticity of employment with respect to output is not constant within each phase of the business cycle and might depend on the maturity of that phase. Nevertheless, empirical evidence is almost non-existent. Using the unemployment gap as the proxy for the maturity of the business cycle phase, this paper seeks to determine heterogeneous elasticity across different business cycle phases. Furthermore, we aim to evaluate specific elasticities for separate demographic groups, considering gender, age, and educational attainment level, to identify the most vulnerable to jobless growth. Our specification is based on the employment version of Okun’s law, and estimates are provided for the whole EU-27 panel covering the period from 2000 to 2022. Our results suggest that elasticity is higher when the unemployment gap is positive and increasing and lower when the gap decreases, regardless of the business cycle phase. Thus, it can be argued that the possibility of growth increasing employment is very limited when the economy operates at its potential level (full employment) for all demographic groups.

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Section: Introductioncontrasting

confidence: 79%

When and for Whom Does Growth Becomes Jobless?

Butkus,

Dargenytė-Kacilevičienė,

Matuzevičiūtė

et al. 2024

Economies

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“…φs,i,tΔYs,i,t. Thus, we are able to isolate the distinct employment at we term as 'employment intensity'), βs, for each sector rather than simply estimating the composite er, βsφs is still interesting since it yields the distinct 'component elasticities' or the 'proportional mployment to change in each sectors' output, i.e., the βsφs estimates show the change in the employment d with a 1% increase in output of sector s.e analysing the relationship between unemployment and output confirms a more robust unemployment ns than expansions(Kim and Park, 2019;Aguiar-Conraria et al, 2020). Results showed asymmetric en labour market variables and GDP within and between recession and expansion phases.…”

mentioning

confidence: 90%

“…, construction (con) and service sector (ser), represents the share of sector s in the country's economy. We assume φ s,i,t as time-varying rather than constant share to ensure the accuracy of the approxim- The literature analysing the relationship between unemployment and output confirms a more robust unemployment reaction to recessions than expansions (Kim and Park, 2019;Aguiar-Conraria et al, 2020). Results showed asymmetric relationships between labour market variables and GDP within and between recession and expansion phases.…”

Section: Model and The Datamentioning

confidence: 99%

Do Gender and Age Matter in Employment – Sectoral Growth Relationship Over the Recession and Expansion

Butkus

Dargenyte-Kacileviciene

Matuzevičiūtė

et al. 2022

ECO

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This paper examines age- and gender-specific employment sensitivity to growth across different economic sectors. By applying a non-linear panel specification of Okun’s first-difference equation on EU-28 countries for 1995-2019, we estimate age-, gender-, and sector-specific employment intensities to growth. Our study examines the ability of growth in different sectors to generate total employment opportunities. Results show that regardless of gender or age, the employment growth is mainly driven by the services sector growth. Still, if we consider the share of a sector in the economy, the construction sector is found to be the most employment-intensive. Our estimates show that the male and female employment intensities of growth in services are quite equal. Considering the employment opportunities by gender, the main differences were found in the construction sector. Expansion and recession were confirmed to have a significantly different effect on the employment rate only in the construction sector regardless of age and gender.

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“…The first advantage of using a wavelet-based model is that wavelets can be used to capture cyclical effects that are not captured in purely time-domain methods. For example, Aguiar-Conraria et al ( 2020 ) utilizes wavelets to improve the estimates of the Okun’s Law specification by capturing the time–frequency structure. Aguiar-Conraria et al ( 2018 ) used wavelet to estimate the Taylor Rule, and found evidence for a shift in the policy focus between the short, intermediate, and long cycles across different time periods.…”

Section: Model Specificationmentioning

confidence: 99%

Resilient Control for Macroeconomic Models

Hudgins

Crowley

2022

Comput Econ

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This paper derives a macroeconomic resilient control framework that provides the optimal feedback fiscal and monetary policy responses in response to a potentially large negative external incident. We simulate the model for the U.S. under the conditions that prevailed throughout the 2020 economic crisis that occurred due to the government lockdown that was caused by the coronavirus pandemic. We develop a discrete-time soft-constrained linear-quadratic dynamic game under a worst-case design with multiple disturbances. Within this context, we introduce a resilience feedback response and compare the case where the policymakers counter in response the external incident with the case when they do not counter. This framework is especially applicable to large-scale macroeconomic tracking control models and wavelet-based control models when formulating the magnitudes of the policy changes necessary for the unemployment rate and national output variables to maintain acceptable tracking errors in the periods following a major disruption. Our policy recommendations include the maintenance of “rainy day” funds at appropriate levels of government to mitigate the effects of large adverse events.

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Okun’s Law across time and frequencies

Cited by 29 publications

References 35 publications

When and for Whom Does Growth Becomes Jobless?

When and for Whom Does Growth Becomes Jobless?

Do Gender and Age Matter in Employment – Sectoral Growth Relationship Over the Recession and Expansion

Resilient Control for Macroeconomic Models

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