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Hours Worked and Permanent Technology Shocks in Open Economies

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Abstract

We use Structural Vector Autoregressions to study the impact of technology improvements on hours worked in the major seven countries. While previous studies estimate the response of labor input to permanent shocks to country-level labor productivity, we consider the response of labor input to aggregate-level labor productivity. Since labor productivities do cointegrate in the G7, the estimated responses should look very similar. They do not: for each country but Germany, the responses estimated using G7 labor productivity sizeably exceed those estimated using country-level labor productivity. These results also hold in larger SVAR models.

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Notes

  1. Accepting this interpretation, Collard and Dellas (2007) and Francis and Ramey (2005), among others, specify flexible-price models able to reproduce a fall in hours following a technology shock.

  2. Our results are similar to those obtained by Galí (2005).

  3. A large number of papers, including Stock and Watson (2005), Canova et al. (2007) and Kose et al. (2008), establish the large contribution of world shocks to aggregate fluctuations. Moreover, Rabanal et al. (2008) have shown that Total Factor Productivity (TFP) cointegrates among major industrialized countries and thus favored the relevance of a world permanent technology shocks.

  4. In Dupaigne and Fève (2009), we estimate and simulate a two-country DSGE model with a permanent world technology shock and stationary country-specific technology and preference shocks. We obtain that country-level SVAR models lead to biased estimation of the true permanent technology shock. We also show that an aggregate measure of labor productivity reduces the bias when it is used instead of domestic ones in SVARs with long run restriction. See also Collard and Dellas (2007) for an open economy setup about the effect of permanent technology shocks on employment.

  5. At the quarterly frequency, only employment data are available on this sample. Our results hold on quarterly employment data (see Dupaigne and Fève 2009).

  6. Endogenous growth models are obvious examples of setups in which non-technology shocks (here, any shock) have long-run effects on labor productivity. Alternatively, Uhlig (2004) emphasizes permanent changes in the capital tax rate or changing attitude towards the workplace.

  7. Hours worked and population numbers are simply the sums of country-level data. To compute aggregate GDP, national accounts data are converted to US dollars using 1995 GDP purchasing power parities (PPPs) for constant price data and current PPPs for data in current prices.

  8. Country-level point estimates are weighted according to the share of each country in total population because we consider per capita productivity and hours worked.

  9. We also perform cointegration tests without any prefiltering of the data and find very similar results. With the latter procedure, we include an intercept in the cointegration equation but none in the VAR.

  10. The country-level labor productivities used in these cointegration tests are expressed in units of local currency at constant price (basically, in units of local good). Hence, they might not be comparable from one country to the other in the short-run. To investigate this issue, we redo the cointegration tests using purchasing power parity (PPP) adjusted labor productivities. The results are identical. Throughout the rest of the paper, we have checked the sensitivity of our results to PPP-adjustment. They remain unchanged.

  11. Due to data availability, their international TFP measures are obtained from the labor input only.

  12. Given the size of our sample, we cannot estimate the 31 parameters of a two lag VAR including both productivity differentials and labor inputs for all countries.

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Correspondence to Martial Dupaigne.

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The views expressed therein are those of the authors and do not necessarily reflect those of the Banque de France.

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Dupaigne, M., Fève, P. Hours Worked and Permanent Technology Shocks in Open Economies. Open Econ Rev 21, 69–86 (2010). https://doi.org/10.1007/s11079-009-9159-z

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