3.2 Trade and Sector Comovement
We next estimate equation (4), the effect of trade on the correlation of a sector’s output
growth with the rest of the manufacturing sector (ρi,A-i). Table 4 presents the cross-
sectional results. Intriguingly, more trade in a sector reduces the correlation of that sector
with the rest of the economy. This negative effect is robust across specifications, although
the significance level is typically not as high as in the volatility regressions, and the mag-
nitude of coefficients not as stable. It is clear that increased exposure to the world cycle
for a sector decouples it from the domestic economy. This covariance effect acts to reduce
the overall variance in the economy, ceteris paribus. Table 5 presents results for the ten-
year panel estimation. The results are broadly in line with those of the cross section, and
robust to the entire battery of fixed effects which we employ. Overall, the effect of trade
on comovement is economically significant, and plausible in magnitude. A one standard
deviation increase in the overall trade results in a decrease in correlation of between 0.07
and 0.14 standard deviations, depending on the coefficient estimate used.
Appendix Tables A5 and A6 present numerous robustness checks using a variety of
different controls and interaction terms. The openness coefficient remains negative and
significant across all specifications, and the point estimates do not vary dramatically relative
to the baseline estimates in Tables 4 and 5, columns (4) and (7) respectively. The properties
of sector-level correlation with the aggregate growth have not been previously studied in the
literature. Therefore, it is much less clear than in the case of sector-level volatility which
additional controls it is important to include alongside the fixed effects. Our approach
here is to use the same battery of robustness checks as we employed in estimating the
sector volatility regressions. We control for average level and growth rate of output, TOT
volatility (both as main effect and interacted with sector-level trade), sector-level volatility
of trade, share of manufacturing trade in total trade, and Raddatz’s interaction of liquidity
needs and financial development. Since we used these before, we do not discuss them in
detail. The coefficient of interest is robust to all of the alternative specifications. We also
run the correlation specifications on the price and quantity per worker variables separately.
Table 6 presents the baseline correlation regressions for quantity per worker and price.
The openness coefficients are all negative and significant. Interestingly, the ranking of the
elasticities of these two variables with respect to trade openness is reversed relative to the
volatility regressions.19
19 Panel estimations are similar to the cross-sectional ones, and are available from the authors upon request.
12