Diversification through trade
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1 Diversification through trade by Francesco Caselli, Miklos Koren, Milan Lisicky and Silvana Tenreyro Discussion by: Fabrizio Perri University of Minnesota and Minneapolis FED ESSIM, May 2009
2 The general question What is the impact of international trade on business cycles (mainly volatility)?
3 The contributions Theory: extend Eaton Kortum set-up with stochastic country specific productivity and shows that more trade generates lower volatility
4 The contributions Theory: extend Eaton Kortum set-up with stochastic country specific productivity and shows that more trade generates lower volatility Quantitative: use the model to assess the impact of observed/counterfactual changes in trade on volatility
5 The contributions Theory: extend Eaton Kortum set-up with stochastic country specific productivity and shows that more trade generates lower volatility Quantitative: use the model to assess the impact of observed/counterfactual changes in trade on volatility Data: present evidence suggesting that decades/countries more trade intense are less volatile
6 Outline of the comments Thoughts on the connection between data and theory Additional evidence on the relation between trade and volatility Possible research directions
7 The mechanism Two countries, hit by a country specific productivity shock z i Under autarky y i z i Var(y i ) Var(z i ) for all i
8 The mechanism Two countries, hit by a country specific productivity shock z i Under autarky y i z i Var(y i ) Var(z i ) for all i Under trade some of the good produced in country i is input of production in country j. So productivity shocks in i affect output/productivity in j and y i (1 α)z i + αz j Var(y 1 ) (1 α) 2 Var(z 1 ) + α 2 Var(z 2 ) + 2cov(z i, z j )
9 The mechanism Two countries, hit by a country specific productivity shock z i Under autarky y i z i Var(y i ) Var(z i ) for all i Under trade some of the good produced in country i is input of production in country j. So productivity shocks in i affect output/productivity in j and y i (1 α)z i + αz j Var(y 1 ) (1 α) 2 Var(z 1 ) + α 2 Var(z 2 ) + 2cov(z i, z j ) Predictions: Trade always increase comovement.
10 The mechanism Two countries, hit by a country specific productivity shock z i Under autarky y i z i Var(y i ) Var(z i ) for all i Under trade some of the good produced in country i is input of production in country j. So productivity shocks in i affect output/productivity in j and y i (1 α)z i + αz j Var(y 1 ) (1 α) 2 Var(z 1 ) + α 2 Var(z 2 ) + 2cov(z i, z j ) Predictions: Trade always increase comovement. Trade might reduce volatility (depends on variance of foreign shocks and on the covariance of foreign and domestic shocks)
11 Evaluating the impact of trade on volatility Need to identify foreign and domestic shocks. Model suggests that foreign shocks can be directly measured as αz j = d ii = IMP ii GO i EXP i when foreigners are productive domestic absorption (IMP ii ) is low rel. to domestic production (so IMP ii is higher) GO i EXP i
12 Evaluating the impact of trade on volatility Need to identify foreign and domestic shocks. Model suggests that foreign shocks can be directly measured as αz j = d ii = IMP ii GO i EXP i when foreigners are productive domestic absorption (IMP ii ) is low rel. to domestic production (so IMP ii GO i EXP i is higher) Once foreign shocks are identified domestic shocks computed residually as z i = y i αz j and can compute also cov(z i, z j )
13 Evaluating the impact of trade on volatility Need to identify foreign and domestic shocks. Model suggests that foreign shocks can be directly measured as αz j = d ii = IMP ii GO i EXP i when foreigners are productive domestic absorption (IMP ii ) is low rel. to domestic production (so IMP ii GO i EXP i is higher) Once foreign shocks are identified domestic shocks computed residually as z i = y i αz j and can compute also cov(z i, z j ) Can ask how much of Var(y 1 ) can be explained by α 2 Var(z 2 ) + cov(z i, z j ).
14 Evaluating the impact of trade on volatility Need to identify foreign and domestic shocks. Model suggests that foreign shocks can be directly measured as αz j = d ii = IMP ii GO i EXP i when foreigners are productive domestic absorption (IMP ii ) is low rel. to domestic production (so IMP ii GO i EXP i is higher) Once foreign shocks are identified domestic shocks computed residually as z i = y i αz j and can compute also cov(z i, z j ) Can ask how much of Var(y 1 ) can be explained by α 2 Var(z 2 ) + cov(z i, z j ). Valid identification but only meaningful if model not misspecified. Also results are a bit all-over the place
15 Trade and the great moderation? Trade and the great moderation? Table 1. Change in Volatility from , for =0.5 Country Percent Change in Standard Deviation (1) Absolute Difference in Variance (2) Absolute Difference in Var(Z) (3) Absolute Difference in Var(dii) (4) Absolute Difference in the Covariance (5) Percent Share of difference (2) accounted for by (4) and (5) Australia Austria Belgiumplus Canada China,P.R.: Mainland Denmark Finland Franceplus Germany Greece India Ireland Italy Japan Korea Mexico Netherlands Norway Portugal Spain Sweden United Kingdom United States
16 More direct evidence in the paper Figure 1: Volatility and Trade-to-Output Shares. (Log) Decade Volatility Decade Average Trade Share lgrs Fitted values The inverse movements in GDP volatility and trade over this period are at o Each dot is a decade, Largest world countries, , annual
17 How robust is the evidence?
18 How robust is the evidence? Volatility (Std of rgdp growth) JAP USA JAP JAP USA JAP USA AUS ESP USA AUS GRC MEX GRC GRC MEX GBR KOR KOR GRC FIN ITA FIN DEU DEU CAN CAN DEU GBR AUS FRA ITA GBR ESP ITA ESPAUS ITAESP GBR FRA FRA KOR MEX SWE NORFIN KOR NOR DNK DNK SWENOR DEU AUT CAN CAN CHE CHE AUT SWE CHE DNK AUT NLD NLD NLD BEL BEL BEL Average trade share Each dot is a decade, OECD countries, , quarterly
19 How about controlling for country/time fixed effects Change in Volatility (Std of rgdp growth) KOR JAP NOR GRC NOR CHE DNK BEL FRA JAP ITA GBR NOR GBR FIN DEU GBR USA USA USA SWE AUS ITA NLD AUS AUS CAN CAN FIN ESP AUT AUT GRC JAP FRA FRA DNK ESP ITA DEU KOR MEX GRC ESP NLD MEX CAN FIN NLD CHE SWE DNK Change in Average trade share KOR BEL DEU AUT Each dot is change between decades, OECD countries,
20 Some numbers Dependent variable is Std of GDP growth: Level Level + FE FD Level Level+FE FD Coeff of Trade (0.52) (2.09) (0.85) (0.69) (3.97) (2.24) Obs Standard errors clustered at the country level are in parentheses
21 Summarizing Some evidence of large negative relation between trade and volatility, but not very robust to change in sample, methodology etc. ("ambiguous at best")
22 Summarizing Some evidence of large negative relation between trade and volatility, but not very robust to change in sample, methodology etc. ("ambiguous at best") This does not mean that the mechanism highlighted in the paper is not a valid one It suggests though that unconditional volatility in a decade strongly affected by events orthogonal to trade (i.e. Asian crises, oil shocks, financial crisis)
23 Trade and comovement Frenkel and Rose have documented strong relation between trade and comovement of output and TFP Kose and Yi have shown that this relation hard to replicate quantitatively in standard business cycle model, in particular hard to obtain that trade leads to more TFP comovement This model suggests that stochastic EKAL might help explain the pattern (also see Burstein, Kurz and Tesar)
24 Conclusions Very nice paper Main contribution in my view is that it proposes an extension of the EKAL model for business cycle analysis Could be a very useful to study shocks propagation and interaction between trade and intertemporal markets
Diversi cation through Trade
Diversi cation through Trade Francesco Caselli, Miklos Koren, Milan Lisicky, and Silvana Tenreyro Very preliminary May 2010 Caselli et al. (Very preliminary) Diversi cation through Trade May 2010 1 / 39
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