This column examines how important these terms-of-trade shocks are in explaining GDP fluctuations. These relative price movements are reflected in movements in the terms of trade, or the relative price of a country's exports in terms of its imports. This view is largely based on the analysis of calibrated business-cycle models.
Essentially, the result is obtained by first estimating a process for the terms of trade and then feeding it to an equilibrium business cycle model to compute the variance of macroeconomic indicators of interest induced by this type of disturbance. Then this predicted conditional variance is divided by the actual observed unconditional variance of the corresponding macroeconomic indicator to obtain the share of variance explained by terms-of-trade shocks.
In this entry, we argue that the picture that emerges from structural vector autoregression SVAR analysis is quite different. To identify terms-of-trade shocks, we assume that movements in the terms of trade are exogenous. This assumption, which has been embraced universally by the existing related literature whether empirical or theoretical, is motivated by the fact that the typical poor or emerging country is too small to affect world relative prices. We define the set of poor and emerging countries as all countries with average PPP converted GDP per capita of less than 25, dollars of over the period The SVAR system contains six variables, output, consumption, investment, the trade balance, the real exchange rate, and the terms of trade.
The sample period is to The country selection is dictated by the requirement of at least 30 consecutive annual observations for all six variables.
Figure 1 presents the variance decomposition implied by the SVAR analysis in the form of a histogram. The horizontal axis measures the share of the variance of the cyclical component of real GDP per capita attributable to terms-of-trade shocks in percent. The horizontal axis is divided into six equally sized bins.
The vertical axis measures the number of countries in each bin. Similar results obtain for the other variables included in the SVAR model. These results suggest that there is a disconnect between theoretical and empirical models when it comes to gauging the importance of terms-of-trade disturbances in generating business cycles.
Explaining this disconnect between empirical and theoretical models is an important item in the research agenda that lies ahead. Its resolution is likely to involve a combination of better empirical and theoretical models as means to interpret the data.
This is likely to be the case especially for countries whose exports or imports are concentrated in a small number of commodities. At the same time, the theoretical model could be amended by assuming that the government uses tax or commercial policy to isolate domestic markets from swings in world prices. In this case, movements in the terms of trade will elicit attenuated incentives to change the domestic allocation of output and absorption. This implies that, in the event of a terms of trade shock, it is likely to be much more important for Mozambique than for Tanzania to alter domestic saving to smooth national consumption, because the former has a much greater chance of experiencing short-lived shocks than the latter.
Also, because the range of the duration of terms of trade shocks experienced by Tanzania is much wider than the range experienced by Mozambique, the variability of shocks is likely to be greater for Tanzania. In contrast, consider the 11 countries that typically experience very long-lived permanent terms of trade shocks.
For these countries, half of the shocks will be finite and half will be permanent. Although these results do not rule out a change in domestic saving as a useful means of smoothing national consumption following terms of trade shocks, these countries are much likelier to experience long-lived shocks, which may make such switches between consumption and saving financially unsustainable.
How large are shocks? While it is particularly important to ascertain the duration of shocks to the terms of trade, knowledge of the typical size of terms of trade shocks is also of great interest. Shocks that are typically small but long lived will have different implications for the setting of macroeconomic policies than large, long-lived shocks.
In this connection, we can measure the size of shocks to the terms of trade, using the standard error of the regression analysis that calculates the duration of terms of trade shocks. As these errors are normally distributed, this implies that two-thirds of the time any change in the terms of trade is within one standard error of the initial level of the terms of trade, and one-third of the time any change is larger than one standard error.
The values for the standard error of the regression for each country are displayed in descending order in Chart 2. The results in Chart 2 reveal that, unlike the typical duration of shocks to the terms of trade, the size of shocks is evenly distributed across African countries, ranging from the smallest shocks South Africa to the largest shocks Equatorial Guinea. What determines the duration of shocks? Despite the common dependence of sub-Saharan economies on commodity exports, the typical duration of terms of trade shocks varies widely from country to country.
What accounts for this? The results of an empirical analysis reveal that terms of trade shocks tend to last longer with everything else held constant for countries with large shares of petroleum imports in total imports because petroleum price shocks tend to be long lived ; with small shares of nonfuel commodity exports in total exports because many nonfuel exports are agricultural commodities, which tend to be subject to short-lived, weather-related supply shocks ; and whose exports are highly concentrated in commodities subject to long-lived price shocks.
Consequently, a country that is an intensive exporter of nonfuel commodities, is a relatively small-scale importer of petroleum products, and has as a major export a commodity subject to short-lived price shocks such as The Gambia, which exports groundnuts will typically experience short-lived shocks to its terms of trade. Alternatively, oil-exporting countries such as Nigeria will typically experience long-lived shocks to their terms of trade, because oil is subject to long-lived price shocks.
Policy implications How might the estimates presented here of the duration and variability of terms of trade shocks be useful to African policymakers in reacting to a particular terms of trade shock? Currently, policymakers probably have little information on which to base an assessment of whether any given shock is likely to be short lived or long lived. Estimates of the average duration and variability of typical shocks can be used, together with episode-specific knowledge of world commodity-price movements, to form a judgment of the likely duration of a terms of trade shock.
The ranges confidence intervals measuring the variability of shock durations are important here, because it is possible to estimate shock duration with some degree of precision for certain countries, whereas for other countries the range of shock durations is wide, indicating a broad range of possible outcomes. Measuring the duration, variability, and size of terms of trade shocks.
Chart 1 presents the estimated average duration and associated range in years of terms of trade shocks for 42 sub-Saharan African countries, ordered by decreasing duration. The measure used to quantify duration is the half-life of a shock—the number of years until the effect of a shock to the terms of trade has diminished to half its original magnitude.
We also calculate the range exact confidence interval surrounding the estimated average duration of shocks as a measure of the variability of the duration of shocks. The average median duration denotes that half of the actual realizations of the duration of shocks will be below the estimated average and half of the actual realizations will exceed it. The range 90 percent confidence interval indicates the span of years that accounts for 90 out of actual realizations of the duration of shocks.
In the majority of cases 26 of the 42 countries , it takes more than two years, on average, for a terms of trade shock to dissipate to half its initial magnitude. Moreover, the range surrounding the average duration of terms of trade shocks was rather wide, indicating that the duration of shocks is quite variable.
The terms of trade shock reduces the marginal product of factors in the exportable sector, and resources shift away from the tradable sector. Nontradable output, however, could either grow or shrink, depending on which dominates—.
How important are terms-of-trade shocks? Stephanie Schmitt-Grohe, Martín Uribe 20 July This column examines how important these terms-of-trade shocks are in explaining GDP fluctuations.
How Important Are Terms Of Trade Shocks? Stephanie Schmitt-Grohé, Martín Uribe. NBER Working Paper No. Issued in June , Revised in November NBER Program(s):International Finance and Macroeconomics According to conventional wisdom, terms of trade shocks represent a major source of business cycles in emerging and poor countries. We show that a shock to the terms of trade can affect the supply of productive factors like labor and that the effects of these shocks, as in the simple examples, also have an ambiguous impact on real GDP at base period prices.
current terms of trade relative to the base period terms of trade. If the current import price is the same as the base period price, then the shock has no effect. Terms of Trade Shocks: What Are They and What Do They Do? are fairly standard. The third shock, a globalisation shock that may result, for instance, from the increasing importance of China, India and eastern Europe in the global economy, is more novel. Determining the underlying source of variation in the terms of trade is shown to be.