Don Davis & James Harrigan provide theoretical grounding for public worries in “Good Jobs, Bad Jobs, and Trade Liberalization”:

Globalization threatens “good jobs at good wages”, according to overwhelming public sentiment. Yet professional discussion often rules out such concerns a priori. We instead offer a framework to interpret and address these concerns. We develop a model in which monopolistically competitive firms pay efficiency wages, and these firms differ in both their technical capability and their monitoring ability. Heterogeneity in the ability of firms to monitor effort leads to different wages for identical workers – good jobs and bad jobs – as well as equilibrium unemployment. Wage heterogeneity combines with differences in technical capability to generate an equilibrium size distribution of firms. As in Melitz (2003), trade liberalization increases aggregate efficiency through a firm selection effect. This efficiency-enhancing selection effect, however, puts pressure on many “good jobs”, in the sense that the high-wage jobs at any level of technical capability are the least likely to survive trade liberalization. In a central case, trade raises the average real wage but leads to a loss of many “good jobs” and to a steady-state increase in unemployment.

NBER working paper.

Dani Rodrik:

Advocates of globalization love to argue that free trade lowers prices, and the argument seems sensible enough. Think of all the cheap goods from China that we can buy at Wal-Mart. But anyone who understands comparative advantage knows that free trade affects relative prices, not the price level (the latter being the province of macro and monetary factors). When a country opens up to trade (or liberalizes its trade), it is the relative price of imports that comes down; by necessity, the relative prices of its exports must go up! Consumers are better off to the extent that their consumption basket is weighted towards importables, but we cannot always rely on this to be the case.

If Rodrik comes to play the same role in the blogosphere that he has in academia, I expect that many free traders will take an extra moment of reflection before hitting “post.”

Kala Krishna and Ling Hui Tan model importers (pdf):

Why is it important to model the role of traders explicitly? We do so not simply to inject a dose of realism into the analysis but because the size of the import industry matters for the amount of trade that takes place and the consequent level of social welfare. And the size of the import industry, in turn, is affected by the costs and risks involved in importing. This is where our model differs from the standard partial equilibrium analysis of trade policy under perfect competition: by explicitly introducing entry costs and an element of uncertainty for all potential traders – factors that are crucial in determining the entry decisions of traders and ultimately, the outcome of trade policies – we show that neglecting the role of traders can lead one astray in evaluating the effects of various trade restrictions. Thus, the fundamental contribution of this paper lies in its implications for trade policy, which differ quite substantially from the norm.

In Free Trade Under Fire, Douglas Irwin points to two examples of large exogenous trade policy shocks that allow us to calculate the static benefits promised by the theory of comparative advantage:

In 1859, a bit of gunboat diplomacy by Commodore Matthew Perry ended two centuries of Japanese autarky and exposed it to foreign trade. Japanese prices converged to world prices, so the country became an exporter of silk and tea while an importer of cotton and woolen goods. Estimates of these gains from trade are as high as nine percent. (Daniel Bernhofen & John Brown, “A Direct Test of the Theory of Comparative Advantage: The Case of Japan,” JPE 2004, pdf; “An Empirical Assessment of the Comparative Advantage Gains from Trade: Evidence from Japan,” AER 2005)

In 1807, President Thomas Jefferson ordered an economic embargo to punish Britain for interfering with American ships on the high seas. This termination of trade raised the domestic price of imported goods by 33 percent and lowered the domestic price of exported goods by 27 percent. The static welfare loss was around five percent. (Douglas Irwin, “The Welfare Cost of Autarky: Evidence from the Jeffersonian Trade Embargo, 1807–09,” RIE 2005)

Neat.

Virginia Di Nino, Rosen Marinov & Nadia Rocha – “Trade Liberalization and New Exporters’ Size: Theory and Evidence”

This paper tests an empirical implication of Melitz (2003) in the context of falling trade costs, using the EU’s intensive liberalization phase (1993−2002) as a natural experiment. Contrary to the model’s predictions, firms that switch from non-exporting to exporting over the studied period are not concentrated in a particular size range. Our findings, based on a rich data set of French manufacturing enterprises, suggest scope for fine-tuning of the theoretical framework.

Available here (pdf).

“One of the fundamental tenets of free trade is that currencies should float — or at the very least, move along with market forces.” True or False? Explain.

Greg Mankiw discusses.

A new NBER working paper by Richard Baldwin and Daria Taglioni looks like an important extension of the Anderson-van Wincoop approach for trade gravity model fans:

This paper provides a minimalist derivation of the gravity equation and uses it to identify three common errors in the literature, what we call the gold, silver and bronze medal errors. The paper provides estimates of the size of the biases taking the currency union trade effect as an example. We generalize Anderson-Van Wincoop’s multilateral trade resistance factor (which only works with cross section data) to allow for panel data and then show that it can be dealt with using time-varying country dummies with omitted determinants of bilateral trade being dealt with by time-invariant pair dummies.

I’ll get a chance to read the paper next week when I have NBER access, and then I’ll know if “Gravity for Dummies” incorporated the “Log of Gravity.”

Brad DeLong:

In the United States, at least, the problem is that most beneficiaries from globalization don’t really know that they are beneficiaries, or how much they benefit.

Brad Setser, via MR:

Walmart’s customers are diffuse and unorganized.  Walmart itself is not.   The customers of US electronics firms that source production in China are diffuse.  But the US firms that make money off the China trade, and benefit from China’s willingness to sell its “assembly services” on the cheap, are a rather concentrated interest. And when it comes to the politics of trade, it seems to me like the customer – represented by the firms that organize global supply chains – usually win, at least on the big issues of real importance to global firms (liberalizing agricultural trade isn’t one of them). 

Richard Baldwin (pdf):

To understand juggernaut liberalisation of intra-industry trade, it is necessary to reach for the very latest trade theories, the so-called new-new trade theory (Melitz 2003, Eaton and Kortum 2002). These models allow for differences in firm size and efficiency and explain why the largest, most efficient firms export while smaller firms sell only domestically. In addition to matching many important aspects of reality, this implies that there is what might be called ‘intra-sectoral special interest politics’. In the new-new trade models, reciprocal trade liberalisation raises the profits of big export firms while lowering the profit of small firms in the same industry that sell only in the local market (Falvey, Greenaway and Yu 2004, Baldwin and Forslid 2004). The intuition is simple. Reciprocal liberalisation harms small firms that sell only locally since it raises the degree of competition they face; they have no exports to benefit from the expanded foreign market access. This leads to a downsizing of such firms with some of them exiting the industry. For the big firms, by contrast, the extra competition at home is offset by better market access abroad. On net they gain since their sales benefit from the downsizing and exit of small firms in both markets. Turning from the economic impact of reciprocal liberalisation to the political economy aspect, the key fact is that there are many more small firms than big firms. Thus, Olsen’s Asymmetry suggests that industries engaged in intra-industry trade will tend to be pro-liberalisation. Notice the juggernaut’s liberalisation-begets-liberalisation features of this mechanism. Big exporting firms drive the liberalisation of sectors marked by intra-industry trade since they are better organised politically than the small firms in the same sector, and the liberalisation itself downsizes the anti-trade small firms while upsizing the pro-trade big firms.

This approach to political economy suggests structural reasons to be optimistic about freer trade, despite the Doha round’s struggles.

I haven’t finished reading “Cleaning Up the Kitchen Sink” (pdf) by Francisco Rodriguez, but the first nine pages are compelling enough for me to pass it along anyway.

Rodriguez goes into the archives to revisit Mankiw-Romer-Weil and the models from which linear regression specifications are derived in growth theory. When authors toss in a vector of variables of interest in addition to the standard measures of initial GDP, human capital, etc, they almost always assume that the variables of interest (malaria, institutions, etc) are linearly related to growth. Of course, that doesn’t jive very well with good economic theory (for example, binding constrants and the theory of the second best). Rodriguez argues that the ad hoc introduction of quadratic terms and interaction variables is not a sufficient remedy.

What if the non-linearity is more complex than what can be captured by a set of simple quadratic and linear interaction terms? As I discuss below, if this is the case then most of the regressions currently estimated suffer from misspecification bias, making the type of inferences commonly drawn from their estimation invalid. Furthermore, the data requirements of estimating truly non-linear functions can be quite demanding and far outstrip the availability of data in currently existing data sets.

This problem is more than a theoretical curiosum. A systematic exploration of the theoretical foundations of the linear growth specification reveals that the set of assumptions necessary to justify fitting a linear function to the data is so restrictive as to practically make the linear specification the true theoretical curiosum. I suggest that the starting framework for an exploration of the growth evidence should be a specification that allows for a general set of interactions between the set of potential production function shifters.

[Hat tip: AdamSmithee]