Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund

Appendix: Description of Other Variables in the CA Regression

Our CA regression augments the latest version of the IMF’s External Balance Assessment Methodology. For completeness, we provide the definitions and sources of the variables used (they can also be downloaded from https://www.imf.org/external/np/res/eba/data.htm).

L.NFA/Y: Lagged net foreign asset to GDP ratio from Lane and Milesi-Ferretti (2018).

L.NFA/Y * (dummy if NFA/Y < –60%): The preceding variable interacted with a dummy that takes the value of 1 when a country’s NFA-to-GDP ratio is less than –60 percent.

L.Output per worker, relative to top 3 economies: Lagged PPP GDP divided by working age population (from the IMF’s World Economic Outlook database) relative to the average of the United States, Japan, and Germany.

L.Relative output per worker * K openness: The preceding variable interacted with capital account openness (from the Quinn database).

Oil and natural gas trade balance * resource temporariness: Difference between exports and imports of oil and natural gas as a percentage of GDP; this factor enters the regression only when the balance is positive. The balance is interacted with a measure of temporariness, which is calculated as the ratio of current extraction to proven reserves (i.e., the inverse of “years until exhaustion”) scaled by the same ratio applicable to Norway in 2010. Higher values of the temporariness term indicate that the resource is expected to be exhausted sooner. Data sources: the IMF’s World Economic Outlook database, the World Bank, and the BP Statistical Review of World Energy.

GDP growth, forecast in 5 years: IMF’s World Economic Outlook’s forecast of the five-year-ahead real GDP growth.

L.Public health spending/GDP: Ratio of public health spending to GDP, based on data from the OECD, the World Bank’s World Development Indicators, the UN Economic Commission for Latin America and the Caribbean, the IMF’s Financial Affairs Department, and the Asian Development Bank.

L.demeaned VIX * K openness: Chicago Board Options Exchange Volatility Index (from Haver Analysis database) interacted with the capital account openness described previously.

Own currency’s share in world reserves: A country’s currency share in world reserves, obtained from IMF and Currency Composition of Official Foreign Exchange Reserves.

L.demeaned VIX * K openness * share in world reserves: Interaction between the preceding two variables.

Output gap: Output gap as estimated by the IMF’s World Economic Outlook.

Commodity ToTgap * trade openness: The commodity terms-of-trade (ToT) index is calculated as the ratio of a geometric weighted average price of 43 commodity export categories to a geometric weighted average price of 43 commodity imports, where both are computed relative to the manufactured goods prices in advanced economies. Weights are given by the commodities’ export and import shares. To derive the cyclical gap, the ToT series is first extended into the medium term (using commodity prices projected by the most recent IMF World Economic Outlook) and then Hodrick–Prescott filtered for each country. The resulting gap is interacted with a measure of the country’s trade openness, defined as the share in GDP of exports plus imports of goods and services.

Institutional/political environment (ICRG-12): Indicator used to gauge institutional and political risk based on factors that include socioeconomic conditions, investment profile, corruption, religious tensions, democratic accountability, government stability, law and order, and bureaucratic quality (from the PRS Group’s International Country Risk Guide).

Detrended private credit/GDP: Private credit detrended using the methodology developed by the Bank for International Settlements (BIS), which considers the role of financial deepening and other low-frequency movements in credit. Sources: BIS credit statistics and the World Bank’s World Development Indicators.

Cyclically adjusted fiscal balance, instrumented: The instrument is generated using a first-stage regression that incorporates the lagged and cyclically adjusted global fiscal balance, a time trend, lagged world GDP growth, lagged domestic and world output gaps, US corporate credit spreads, exchange rate regimes, the polity index, and the average cross-sectional fiscal balance.

(∆Reserves)/GDP * K controls, instrumented: Change in central bank foreign exchange reserves scaled by nominal GDP, both in US dollars. The first-stage regression includes M2/GDP, US interest rates, and global reserve accumulation with country-specific slopes in order to account for various reserve accumulation motives. Sources: IMF’s World Economic Outlook, Lane and Milesi-Ferretti (2018), and IMF’s Data Template on International Reserves and Foreign Currency Liquidity.

Dependency ratio: Old-age dependency ratio (ages 65+/ages 30–64), from UN World Population Prospects.

Population growth: From UN World Population Prospects.

Prime savers share: Share of prime savers (ages 45–64) as a proportion of the total working-age population (ages 30–64), from UN World Population Prospects.

Life expectancy at prime age: Life expectancy of a current prime-aged saver, from UN World Population Prospects.

Life expectancy at prime age * future dep. ratio: Interaction between future old age dependency ratio (computed as a moving average of the ratio 15–25 years forward) and life expectancy at prime age (as defined previously).

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1

We thank JaeBin Ahn, Diego Cerdeiro, Luis Cubeddu, Russell Green, Hiau Looi Kee, Andrei Levchenko, Maurice Obstfeld, Jonathan Ostry, and Petia Topalova for their generous comments and feedback as well as Steven Wu Chaves for excellent research assistance. The views expressed in this paper are those of the authors and do not necessarily represent the views of the IMF, the IDB, their Executive Boards, or their management.

1

International trade in services is generally associated with higher costs than manufacturing trade because it is more sensitive to natural inhibiting factors such as geographical distance and cultural differences; it can also face high policy-related barriers, including regulatory requirements (Miroudot, Sauvage and Shepherd 2013).

2

According to Governor Carney of the Bank of England: “One cause of global imbalances is the uneven playing field between trade in goods and services, with barriers to services trade currently up to three times higher. . . . Most of the world’s major surplus economies, like Germany and China, are net exporters of goods and benefit from this asymmetry. Conversely, countries with comparative advantage in services, like [the] US and [the] UK, are more likely to run current account deficits.” (“A Fine Balance,” speech at the Mansion House, London, 20 June 2017.

3

Anderson and Neary (2005) explain that the choice between frictionless and actual trade weights is equivalent to the choice between Laspeyres and Paasche price indices; the former index relies on a fixed basket, whereas the latter fully reflects the substitution that occurs following a price change.

4

Another related strand of literature focuses on understanding the costs to trade in services. For example, Ger-vais and Jensen (2013) and Anderson, Milot, and Yotov (2014) examine services trade within the United States and between the United States and Canada (respectively); these authors find that geographical distance is itself a substantial impediment. Our paper’s approach is also similar to that of Anderson et al. (2015), which estimate a structural gravity equation using detailed data on services trade and production.

5

Any home bias in product preferences would appear in the source country-specific variables (e.g., cij,zij).

6

In Section 3.2 we shall incorporate directional observables into the structural gravity estimation.

7

Our use of the Poisson pseudo-maximum likelihood method means that our comparative advantage estimates are closer to those proposed by French (2017) than to those proposed by Costinot, Donaldson, and Komunjer (2012).

10

These series on exchange rates, along with all of the current account regressors (except for those pertaining to trade costs), are available from the External Balance Assessment website (https://www.imf.org/external/np/res/eba/data.htm).

11

The results for common currencies might not be generalizable because the eurozone is our sample’s only currency union.

12

To preserve space, these figures report only those estimates that use lagged trade weights and are based on the Johnson and Noguera (2017) data set.

13

The most recent version of the EBA current account regression covers the period 1986–2016; hence its overlap with our data sets from Johnson and Noguera (2017) and the 2016 WIOD is, respectively, 1986–2009 and 2000–2014.

14

However, this hypothetical scenario of a 10 percentage point decline in the costs of exporting is not a counterfactual based on a full general equilibrium because it does not take into account any wage or price responses. It also does not incorporate a commensurate reduction in the country’s costs of importing.

15

Effective trade costs are calculated using lagged trade weights, so the corresponding coefficients are based on column (4) of Tables II and III. Results based on frictionless trade weights are reported in Annex XXX.

16

We also try including a bilateral measure of temporary trade barriers, as described in Section 2.2. We find that this variable has little explanatory power, which is not surprising in light of the small share of trade flows affected by such barriers.

17

There are two other reasons for excluding bilateral tariffs in our baseline gravity estimations. First, doing so would reduce the sample size because we have no bilateral sectoral tariff data before year 1995. Second, our baseline specification is more flexible in that it does not require that the import demand elasticity of tariffs be the same across importer-exporter pairs.

18

We also examine the role of safeguards—a type of temporary trade barrier that is applied unilaterally by importers—and find that its coefficient is not statistically significant.

19

Some of the measures underlying the OECDs indices apply to both domestic and foreign firms. Such across-the board barriers could worsen a countrys comparative advantage through their adverse impact on productivity of domestic firms and may not necessarily translate into higher trade costs to import. They would, however, constitute nondiscriminatory trade barriers to the extent that they affect foreign firms disproportionally more.

20

To be consistent with the construction of estimated nondiscriminatory trade barriers, this analysis uses each country’s average STRI relative to that of the US.

Effective Trade Costs and the Current Account: An Empirical Analysis
Author: Ms. Emine Boz, Ms. Nan Li, and Hongrui Zhang