Imperfect mobility of labor across sectors and fiscal transmission

Abstract

Our paper investigates the impact of government spending shocks on relative sector size and contrasts the effects across countries. Using a panel of sixteen OECD countries over the period 1970-2007, our VAR evidence shows that a rise in government consumption i) increases the share of non tradables in labor and real GDP while lowering the share of tradables, and ii) causes a significant increase in non traded wages relative to traded wages. While the first finding reveals that the non traded sector is more intensive in the government spending shock and experiences a labor inflow that increases its relative size, the second finding suggests the presence of labor mobility costs preventing wage equalization across sectors. These labor mobility costs appear to play a key role in determining changes in relative sector size across time and space. Whilst the responses of intersectoral labor reallocation and sectoral shares are found empirically to decline over time, the share of non tradables increases more in countries where the degree of labor mobility across sectors is higher. To account for our evidence, we develop an open economy version of the neoclassical model with tradables and non tradables. Our quantitative analysis shows that the open economy model is successful in replicating the responses of sectoral output shares to a fiscal shock, as long as we allow for a difficulty in reallocating labor across sectors along with adjustment costs to capital accumulation. Finally, calibrating the model to country-specific data, we are able to generate a cross-country relationship between the degree of labor mobility and the responses of sectoral output shares which is similar to that in the data. We are grateful to Agustin Benetrix for sharing RATS codes and to Luisito Bertinelli who provided invaluable help at different stages of the paper. We thank Benjamin Born, Falko Juessen, Gernot Müller for providing us with the dataset they constructed containing forecasts for government spending and Laura González Cabanillas for the dataset covering time series for the budget balance-GDP ratio forecast. We are grateful to Francisco Alvarez-Cuadrado, Christophe Hurlin, Stefan Schubert, Stephen Turnovsky for very helpful comments. We have also benefited from suggestions by participants at seminars and conferences. Obviously, any remaining shortcomings are our own. ,where 0 < ϕ J < 1 is the weight of the investment traded input and φ J corresponds to the elasticity of substitution between traded good and non traded good inputs.Since we focus on the long-run equilibrium, the tilde is suppressed for the purposes of clarity. the traded good and the non traded good according to a constant-returns-to-scale function which is assumed to take a CES form:,where ι is the weight of the investment traded input (0 < ι < 1) and φ J corresponds to the intratemporal elasticity of substitution in investment between traded and non traded inputs. The index J T is defined as a CES aggregator of home-produced traded inputs, J H , and foreign produced t...

Sectoral Fiscal Multipliers and Technology in Open Economy

“…Using data from the World Input-Output Database (WIOD) [2013], [2016], we constructed time series for sectoral government consumption and find empirically that the non-traded sector receives on average 80% of government consumption (see column 4 of Table 1). 4 As demonstrated in Online Appendix R.1, see also Cardi et al [2020], Proebsting [2022], when the intensity of the non-traded sector in the government spending shock, denoted by ω G N , is higher than the share of non-tradables in GDP (which averages 64%, see column 1 of Table 1), the demand shock moves productive resources toward the non-traded sector, as long as technology is kept fixed. The impact of the biasedness of the demand shock toward non-tradables can be neutralized however if the rise in G t leads to endogenous TFP gains which vary across sectors.…”

“…Since this industry is non-tradables, the counterpart is government consumption on non-tradables. See Cardi, Restout and Claeys [2020] for more details. The advantage of this database over WIOD is that the sum of G T and G N is very close to government final consumption expenditure time series provided by the OECD that we use to identify shocks to government consumption in section 2 of the main text.…”

“…As exemplified by D' Alessandro et al [2019], Jørgensen and Ravn [2022], Antolin-Diaz and Surico [2022], Klein and Linnemann [2022], the literature highlighting the technology channel of fiscal policy remains distinct from a second strand emphasizing the role of the sector's intensity in the government spending shock and barriers to mobility in determining sectoral and aggregate fiscal multipliers, see e.g., Boehm [2020], Bouakez et al [2022b], Cardi et al [2020], Cox et al [2020], Lambertini and Proebsting [2022], Proebsting [2022].…”

“…Benetrix and Lane [2010] document evidence which reveals that a government spending shock disproportionately increases non-traded value added. As shown by Cardi et al [2020] and Lambertini and Proebsting [2022], to account for the fiscal transmission mechanism, the open economy model with tradables and non-tradables must allow for both a non-traded bias in government spending and imperfect mobility of labor across sectors.…”

“…The solid blue line shows the sectoral effects when estimating the VAR model over 1970-2007 for 16 OECD countries while the dashed blue line with triangles shows estimates when we estimate the same VAR model over 1970-2015 for 18 OECD countries. The solid blue line shows results obtained byCardi, Restout and Claeys [2020].Sample: 18 OECD countries, 1970…”