How Important Are Terms of Trade Shocks? Stephanie Schmitt-Groh´ e Mart ´ ın Uribe Columbia University October 28, 2015 1
Conventional View: Terms-of-trade shocks are a major source of business-cycle fluctuations in poor and emerging countries. (ex: Mendoza, IER 1995; Kose, 2002.) This paper: Terms-of-trade shocks explain on average only about 10 percent of the variance of output in poor and emerging countries. 2
The Terms of Trade: tot t = P x t P m t tot t = terms of trade. P x t = price of exports. P m = price of imports. t 3
Mendoza (IER, 1995): “Results show that terms-of-trade shocks account for nearly 1/2 of actual GDP variability.” Methodology: 1. Collect annual terms-of-trade data from 23 developing countries. Sample period is 1960 to 1990. HP filter log of tot t . Compute serial correlation and standard deviation of tot t . Then take averages (means) across countries. This yields: corr ( tot t , tot t − 1 ) = 0 . 414 std ( tot t ) = 0 . 1177 2. Build a theoretical model with 3 sectors, exportables, importables, and nontradables. Calibrate the model. Assume that tot t is exogenous to the country and follows a univariate process with serial correlation 0.414 and standard deviation 0.1177. 4
3. Compute the standard deviation of output under the assumption that terms-of-trade shocks are the only source of uncertainty. This yields std( GDP model ). t 4. Compare std( GDP model ) with the cross-country average standard t deviation of GDP observed in his panel. Mendoza (1995) finds std ( GDP model ) t ) = 0 . 56 std ( GDP data t Thus, terms-of-trade shocks explain 31 percent (= 0 . 56 2 × 100) of the variance of GDP. 5
Observations on Standard Methodology • The finding that TOT shocks explain over 1/3 of the variance of output is obtained in the context of highly stylized structural model (essentially, an open-economy version of the RBC model). • The methodology relies on the theoretical model representing a reasonable approximation to the actual transmission mechanism of TOT shocks. This, aspect, however, is typically unexplored. An Alternative Methodology: SVAR Analysis • The SVAR approach presented here uses the same restrictions to identify TOT shocks, but allows for a more flexible specification of the transmission mechanism. 6
Part I: SVAR Analysis 7
Empirical Model � � ′ . � � � � • Let x t = tot t , tb t , y t , � c t , � i t , RER t • VAR: x t = A x t − 1 + u t u t = Π ǫ t • Identification of ToT shocks: ǫ t ∼ (0 , I ) Π 1 ,j = 0 for j = 2 , . . . , 6 • ToT process is univariate: A 1 ,j = 0 for j = 2 , . . . , 6 • All variables (except tb t ) are log-quadratically detrended. • Estimate the SVAR country-by-country using OLS. 8
Data: • Include all poor and emerging countries that have at least 30 consecutive annual observations of output, consumption, investment, net exports, the terms of trade, and the real exchange rate in the World Bank’s WDI database. • Poor and emerging countries are defined as countries with average PPP-converted GDP per capita in U.S. dollars of 2005 over the period 1990 to 2009 below 25,000 dollars. • 38 countries satisfy both criteria. Algeria, Argentina, Bolivia, Botswana, Brazil, Burundi, Cameroon, Central African Republic, Colombia, Congo, Dem. Rep., Costa Rica, Cote d’Ivoire, Dominican Republic, Egypt, Arab Rep., El Salvador, Ghana, Guatemala, Honduras, India, Indonesia, Jordan, Kenya, Korea, Rep., Madagascar, Malaysia, Mauritius, Mexico, Morocco, Pakistan, Paraguay, Peru, Philippines, Senegal, South Africa, Sudan, Thailand, Turkey, and Uruguay. 9
• Sample period: 1980-2011 (32 years). • Our sample of 38 countries. tot t − 1 + σ tot ǫ tot ǫ tot � tot t = ρ � t ; ∼ (0 , 1) t Estimate ρ and σ tot country by country σ tot √ ρ 1 − ρ 2 Median 0.52 0.10 Interquartile Range [0 . 41 , 0 . 61] [0 . 09 , 0 . 13] 10
Impulse Response to A 10% Increase in the Terms of Trade SVAR Evidence, Median across 38 countries Terms of Trade Trade Balance Output 10 0.6 0.5 0.5 0.4 % dev. from GDP trend 8 % dev. from trend % dev. from trend 0.4 0.3 6 0.3 0.2 0.2 0.1 4 0.1 0 2 0 −0.1 0 −0.1 −0.2 0 5 10 0 5 10 0 5 10 Consumption Investment Real Exchange Rate 0.3 1.2 0.5 0.2 1 0 % dev. from trend % dev. from trend % dev. from trend 0.1 0.8 −0.5 0 0.6 −0.1 0.4 −1 −0.2 0.2 −1.5 −0.3 0 −0.4 −0.2 −2 0 5 10 0 5 10 0 5 10 11
Observations on the estimation results: • half-life of TOT shock is just 1 year. • R 2 of tot equations is modest on average, 30 percent • HLM effect (i.e., tb ↑ in response to a ToT appreciation) hold in 29 out of the 38 countries. • On average, increase in GDP is 0.4 percent on impact. • On average, c and i increase with a one-year delay. • Tot appreciation leads to an appreciation of the real exchange rate. 12
Share of Variance Explained by Terms of Trade Shocks: SVAR Evidence tot tb y c i RER Median 100 12 9 10 14 10 Median Absolute Deviation 0 7 7 6 7 11 13
Share of Variance of Output Explained by Terms of Trade Shocks 20 Algeria 18 Bolivia Burundi 16 C. African R. Congo, DR 14 Costa Rica El Salvador Number of Countries 12 Ghana Brazil Guatemala Cameroon 10 Honduras Colombia Kenya Dominican R. 8 Korea, Rep. India Madagascar Jordan 6 Malaysia Mexico Mauritius Peru 4 Morocco Philippines Pakistan South Africa 2 Paraguay Thailand Argentina Sudan Botswana Senegal Turkey Indonesia Uruguay Cote d’Ivoire Egypt 0 0 10% 20% 30% 40% 50% 60% Share of Variance of Output Explained by TOT Shocks (percent) 14
Summary of SVAR Approach • On average, TOT shocks explain 10 percent of the variance of output in poor and emerging countries. • In only 5 countries (Botswana, Egypt, Cote d’Ivoire, Sudan, and Uruguay) do ToT shocks explain more than 30 percent of the variance of output. • Thus, the SVAR evidence is at odds with the conventional wisdom according to which ToT shocks account for a large share of output variability in poor and emerging markets. 15
Part II : Use a structural model to assess the importance of ToT shocks. Estimate some model parameters country-by-country using data from same 38 emerging and poor countries used in the SVAR. 16
The Theoretical Model • small open economy that takes terms of trade as given. • 3 sectors of production: exportable goods, importable goods, nontradable goods, with variable capital and labor inputs. • Similar to Mendoza (IER,1995) but with more flexibility: —Capital in the nontraded sector can vary over time. —Labor in the importable and exportable sectors can vary. —Investment goods have a domestically produced component. —Allow for sector specificity in capital and labor. 17
The household problem: Preferences: ∞ � β t U ( c t , h m t , h x t , h n E 0 t ) t =0 Budget constraint: c t + i m t + i x t + i n t + p τ t d t +Φ m ( k m t +1 − k m t )+Φ x ( k x t +1 − k x t )+Φ n ( k n t +1 − t ) = p τ t d t +1 k n 1+ r t + w m t h m t + w x t h x t + w n t h n t + u m t k m t + u x t k x t + u n t k n t 18
Final Goods Production 1 � � t ) 1 − 1 t ) 1 − 1 1 − 1 y f χ τ ( a τ µτn + (1 − χ τ ) ( a n µτn , t = µτn y f t = final goods. a τ t = composite of traded goods. a n t = nontraded goods. µ τn = elasticity of substitution between T and N goods. χ τ = expenditure share on tradables if µ τn . 19
Production of the Tradable Composite Good 1 � � 1 1 1 t ) 1 − t ) 1 − a τ χ m ( a m µmx + (1 − χ m ) ( a x 1 − t = µmx µmx a τ t = composite of traded goods. a m t = importable goods. a x t = exportable goods. µ mx = elasticity of substitution between importables and exportables. χ m = expenditure share if µ mx = 1. 20
Production of Importable Goods = A m ( k m ) α m ( h m ) 1 − α m y m t y m = quantity of importable goods produced domestically. t A m = level of productivity in the importable sector. k m = capital input in the importable sector. t h m t = labor input in the importable sector. 1 − α m = labor share in the importable sector. 21
Production of Exportable Goods t = A x ( k x ) α x ( h x ) 1 − α x y x y x t = quantity of exportable goods produced. A x = level of productivity in the exportable sector. k x t = capital input in the exportable sector. h x t = labor input in the exportable sector. 1 − α x = labor share in the exportable sector. 22
Production of Nontradable Goods t = A n ( k n ) α n ( h n ) 1 − α n y n y n t = quantity of nontraded goods produced. A n = level of productivity in the nontradable sector. k n t = capital input in the nontradable sector. h n t = labor input in the nontradable sector. 1 − α n = labor share in the nontraded sector. 23
To ensure a stationary equilibrium process for external debt, we assume that the country interest-rate premium is debt elastic, r t = r ∗ + p ( d t +1 ) 24
Terms of Trade Process � tot t � � tot t − 1 � + σ tot ǫ tot ǫ tot ln = ρ ln t ; ∼ (0 , 1) t tot tot tot > 0. ρ ∈ ( − 1 , 1). σ tot > 0. 25
Functional Form Assumptions � � e d − ¯ d − 1 p ( d ) = ψ Φ j ( x ) = φ j 2 x 2 ; j = m, x, n 26
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