increase in importance over time: the impact of the same trade opening on aggregate
volatility in the 1990s is double what it was in the 1970s. While our approach is silent on
how or whether the nature of the underlying shocks has changed over this period, it is clear
that trade has become an increasingly important conduit for their transmission through the
world economy.4
To summarize, all three channels — sector-level volatility, comovement, and special-
ization — have a sizeable impact on aggregate volatility. It appears, however, that the
comovement effect, which acts to reduce volatility, is considerably less important in magni-
tude than the other two. Thus, the net effect of trade in our data is to increase aggregate
volatility, by raising both sector-level volatility and specialization.
We use data on production, quantity indices, employment, and prices for the manufac-
turing sector from United Nations Industrial Development Organization (2005), and com-
bine them with the World Trade Database (Feenstra et al. 2005) for the period 1970-99.
The resulting dataset is a three-dimensional unbalanced panel of 59 countries, 28 manufac-
turing sectors, and 30 years.5 Our approach has several advantages over the more traditional
country-level analysis. First and foremost, the use of industry-level data makes it possible
to estimate the individual channels for the effect of trade on volatility, something which has
not been done before in the literature. Second, our three-dimensional panel allows us to
include a much richer array of fixed effects in order to control for many possible unobserv-
ables and resolve most of the omitted variables and simultaneity concerns in estimation.
In addition to country, sector, and time effects, we can control for time-varying sector or
country characteristics, or characteristics of individual country-sector pairs. Third, besides
looking at the volatility of GDP per capita (the standard measure used in previous studies),
we are also able to look at other outcome variables, such as quantity, employment, and price
volatility at the industry level to further check robustness.
This paper is part of a growing literature which studies the determinants of volatility,
and its subcomponents, using industry-level data. Most papers, however, focus on the
determinants of one of the mechanisms we consider. For instance, Imbs and Wacziarg
(2003) and Kalemli-Ozcan, S0rensen and Yosha (2003) explore the patterns of specialization,
while Raddatz (2005) and Imbs (2006) study sector-level volatility. Krebs, Krishna and
Mahoney (2005) use Mexican data at the individual level and examine the impact of trade
4 Note that this finding is not at all inconsistent with the common observation that aggregate volatility
itself has diminished over the same time period, which is also true in our data.
5 The UNIDO database does not contain information on non-manufacturing sectors. Unfortunately, this
limitation most probably leads to an understatement of the impact of openness on volatility for those
countries which rely heavily on commodity exports, and are thus more vulnerable to global price shocks
(Kose 2001). On the other hand, by examining the manufacturing sector alone we are able to focus on a
sector that is generally considered key to a country’s development process.