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I. INTRODUCTION For the most part of the last two decades Germany suffered from a hangover of the reunification boom, an overvalued exchange rate, high unemployment, and low growth--so The Economist famously named it the "Sick Man of Europe." At the same time, German companies were relocating production, restructuring, and offshoring. The general public associated such offshoring activities--not only in Germany--with plant closures which made the headlines and confirmed the perception that offshoring was a job killer.1 What usually does not make the news is that such downsizing effects of offshoring may be counterbalanced by productivity effects in the restructuring firm. Depending on their relative size, employment changes are likely to be heterogeneous across offshoring firms. Moreover, possible indirect employment effects on local suppliers and competitors further complicate the picture. The theoretical literature has distinguished two main channels through which offshoring can impact domestic employment (Kohler and Wrona 2011) (2): a positive productivity effect from cost savings and gains in competitiveness which allows firms to increase market shares as well as employment and a negative downsizing effect from the relocation of production processes abroad. In addition to these direct effects there may be indirect ones on those firms that do not offshore. In particular, offshoring firms might substitute domestic suppliers for foreign ones (supplier-substitution effect) and increase their market share at the cost of less competitive, domestic competitors (business-stealing effect). (3) This article proposes a way to estimate these different channels through which offshoring may affect employment, using a representative sample of German establishments, covering the years 1998 to 2004 and 16 sectors. We identify heterogeneous employment changes by different behaviors of offshoring firms, learn about different adjustment scenarios for employment, and estimate an overall effect, which accounts for indirect effects on nonoffshoring firms. Our measure of offshoring is the increase in an establishment's (4) intermediate inputs from abroad. This is the result of either (1) relocating parts of production to foreign affiliates (vertical foreign direct investment [FDI]) or (2) purchasing these inputs from foreign suppliers (international outsourcing). (5) Offshoring is measured at the plant level through a (qualitative) increase of a plant's share of foreign intermediate inputs in total inputs. The use of a plant-level measure of offshoring has advantages over using industry-level measures. Even within narrowly defined sectors, there is considerable heterogeneity in trade flows and the use of imported intermediate inputs that cannot be captured by industry-level measures. Thus, industry measures might suffer from an aggregation bias, whereas firm-level information can serve to identify direct and indirect effects of offshoring on employment. We employ a difference-in-differences matching estimator, a nonparametric estimator that differs from a standard difference-in-differences estimator in the weighting function. Based on the propensity scores, the matching estimator gives those observations of the control group a bigger weight in the regression that are according to pretreatment characteristics similarly likely to receive treatment as a treated observation. There are several applications of difference-in-differences matching estimators in international trade, but to the best of our knowledge this is the first paper on offshoring that discusses how interactions between the control and treatment group can affect the estimated average treatment effects and violate the stable unit treatment value assumption (SUTVA). This article adds to the offshoring literature by looking at different adjustment scenarios that can occur with offshoring decisions. Thereby, we identify different channels of offshoring on employment by varying the treatment and control groups. … |
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