This article estimates a dynamic structural model of firm R&D investment in twelve Swedish manufacturing industries and uses it to measure rates of return to R&D and to simulate the impact of trade restrictions on the investment incentives. Export market profits are a substantial source of the expected return to R&D. R&D spending is found to have a larger impact on firm productivity in the export market than in the domestic market. Counterfactual simulations show that trade restrictions lower both the expected return to R&D and R&D investment level, thus reducing an important source of the dynamic gains from trade. A 10% tariff on Swedish exports reduces the expected benefits of R&D for the median firm by 18.6% and lowers the amount of R&D spending by 7.6% in the high-tech industries. The corresponding reductions in the low-tech industries are 20.6% and 5.5%, respectively. R&D adjustments in response to export tariffs mainly occur on the intensive, rather than the extensive, margin.

This article estimates a dynamic structural model of discrete Research and Development (R&D) investment and quantifies its cost and long-run benefit for German manufacturing firms. The model incorporates linkages between R&D choice, product and process innovations, and future productivity and profits. The long-run payoff to R&D is the proportional difference in expected firm value generated by the investment. It increases firm value by 6.7% for the median firm in high-tech industries but only 2.8% in low-tech industries. Simulations show that reductions in maintenance costs of innovation significantly raise investment rates and productivity, whereas reductions in startup costs have little effect.

This article investigates how a firm's financial strength affects its dynamic decision to invest in R&D. We estimate a dynamic model of R&D choice using data for German firms in high-tech manufacturing industries. The model incorporates a measure of the firm's financial strength, derived from its credit rating, which is shown to lead to substantial differences in estimates of the costs and expected long-run benefits from R&D investment. Financially strong firms have a higher probability of generating innovations from their R&D investment, and the innovations have a larger impact on productivity and profits. Averaging across all firms, the long run benefit of investing in R&D equals 6.6 percent of firm value. It ranges from 11.6 percent for firms in a strong financial position to 2.3 percent for firms in a weaker financial position.

In this paper we develop a structural empirical model that allows us to estimate the impact of R&D on firm profitability through two channels. In the first channel, R&D investment by the firm can impact the firm's production efficiency and lower its marginal cost. This productivity channel raises the firm's sales and profits in both the domestic and export market. The second channel is specific to exporting firms where R&D acts to increase the demand for the firm's products in foreign markets. Using micro data for Swedish manufacturing firms from 2000-2010 we estimate the impact of R&D investment on the unobserved component of the firm's productivity and export market demand. Our empirical results show that firm R&D investment has a statistically significant, positive effect on both the future productivity and the future export demand of the firm. For high-tech industries, we find that the impact of R&D investments on the demand shocks is twice as large as its impact on productivity. On the other hand, the impact of R&D investments on productivity in the low-tech industries is higher than on demand shocks.

This article investigates how a firm's financial strength affects its dynamic decision to invest in R&D. We estimate a dynamic model of R&D choice using data for German firms in high-tech manufacturing industries. The model incorporates a measure of the firm's financial strength, derived from its credit rating, which is shown to lead to substantial differences in estimates of the costs and expected long- run benefits from R&D investment. Financially strong firms have a higher probability of generating innovations from their R&D investment, and the innovations have a larger impact on productivity and profits. Averaging across all firms, the long run benefit of investing in R&D equals 6.6 percent of firm value. It ranges from 11.6 percent for firms in a strong financial position to 2.3 percent for firms in a weaker financial position.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

We study differences in the returns to R&D investment between German manufacturing firms that sell in international markets and firms that only sell in the domestic market. Using firm-level data for five high-tech manufacturing sectors, we estimate a dynamic structural model of a firm's discrete decision to invest in R&D and use it to measure the difference in expected long-run benefit from R&D investment for exporting and do-mestic firms. The results show that R&D investment leads to higher rates of product and process innovation among exporting firms and these innovations have a larger economic return in export market sales than domestic market sales. As a result of this higher payoff to R&D investment, exporting firms invest in R&D more frequently than domestic firms, and this endogenously generates higher rates of productivity growth. We use the model to simulate the introduction of export and import tariffs on German exporters, and find that a 20 % export tariff reduces the long-run payoff to R&D by 24.2 to 46.9 % for the median firm across the five industries. Overall, export market sales contribute significantly to the firm's return on R&D investment which, in turn, raises future firm value, providing a source of dynamic gains from trade.

Conflict and Cooperation in Cyberspace: The Challenge to National Security. Edited by Panayotis A. Yannakogeoros and Adam B. Lowther. Boca Raton, FL: Taylor and Francis Group, 2014. ISBN 978-1-4665-9201-8. Tables. Figures. Sources cited. Index. Pp. xxviii, 332.

This paper investigates empirically rm investment behavior in research and development (R&D). Firms make investments in R&D in order to produce innovations. These innovations in turn improve the rm s future productivity level, pro tability and incentives to invest in R&D. Using German rm-level data from the manufacturing sector, we estimate a dynamic, structural model of the rm s choice to invest in R&D and quantify the bene t and cost of engaging in R&D. We nd that among rms that engage in R&D, process and product innovations create a signi cant improvement in their productivity. The cost for performing R&D differs across rms based on their size and R&D history. We compute the bene ts of R&D investment to the rm and nd that by taking the dynamic nature of the investment into account the real return to R&D is several times higher than the one time gain in rm productivity.

Empirical analysis of firm-level investment in research and development (RD) and its effect on innovation patterns and productivity has advanced as a result of innovation surveys in many countries. The weak link in the analysis of these surveys is the empirical model of firm RD choice. In this paper we summarize how a dynamic, structural model of firm investment can be used to estimate firm demand for RD with the data collected in innovation surveys. The estimates provide a natural measure of the expected benefit to the firm of investing in RD. They also allow the researcher to simulate how the firms RD investment will respond to factors that shift cost or demand such as a policy change designed to subsidize RD expenditures or provide financial support to firms with less favorable access to capital markets.

Using firm-level data from the German manufacturing sector, we estimate a dynamic, structural model of the firm's decision to invest in R&D and quantify the cost and longrun benefit of this investment. The model incorporates and quantifies linkages between the firm's R&D investment, product and process innovations, and future productivity and profits. The dynamic model provides a natural measure of the long-run payoff to R&D as the difference in expected firm value generated by the R&D investment. For the median productivity firm, investment in R&D raises firm value by 3.0 percent in a group of hightech industries but only 0.2 percent in low-tech industries. Simulations of the model show that cost subsidies for R&D can significantly affect R&D investment rates and productivity changes in the high-tech industries.

This article estimates a dynamic, structural model of entry and exit for two US service industries: dentists and chiropractors. Entry costs faced by potential entrants, fixed costs faced by incumbent producers, and the toughness of short‐run price competition are important determinants of long‐run firm values, firm turnover, and market structure. In the dentist industry entry costs were subsidized in geographic markets designated as Health Professional Shortage Areas (HPSA) and the estimated mean entry cost is 11 percent lower in these markets. Using simulations, we find that entry cost subsidies are less expensive per additional firm than fixed cost subsidies.

In this article, we use micro data on both trade and production for a sample of large Chinese manufacturing firms in the footwear industry from 2002 to 2006 to estimate an empirical model of export demand, pricing, and market participation by destination market. We use the model to construct indexes of firm-level demand, marginal cost, and fixed cost. The empirical results indicate substantial firm heterogeneity in all three dimension with demand being the most dispersed. The firm-specific demand and marginal cost components account for over 30% of market share variation, 40% of sales variation, and over 50% of price variation among exporters. The fixed cost index is the primary factor explaining differences in the pattern of destination markets across firms. The estimates are used to analyse the supply reallocation following the removal of the quota on Chinese footwear exports to the EU. This led to a rapid restructuring of export supply sources on both the intensive and extensive margins in favour of firms with high demand and low fixed costs indexes, with marginal cost differences not being important.

ABSTRACT While there is widespread empirical evidence indicating exporting producers have higher productivity than nonexporters, the mechanisms that generate this pattern are less clear. One view is that exporters acquire knowledge of new production methods, inputs, and product designs from their international contacts, and this learning results in higher productivity for exporters relative to their more insulated domestic counterparts. Alternatively, the higher productivity of exporters may simply reflect the self-selection of more efficient producers into a highly competitive export market. In this paper we use micro data collected in the manufacturing censuses in South Korea and Taiwan to study the linkages between a producer’s total factor productivity and choice to participate in the export market. We find differences between the countries in the importance of selection and learning forces. In Taiwan, transitions of plants in and out of the export market reflect systematic variations in productivity as predicted by self-selection models. Plants with higher productivity, ex ante, tend to enter the export market and exporters with low productivity tend to exit. Moreover, in several industries, entry into the export market is followed by relative productivity improvements, a result consistent with learning-by-exporting forces. In South Korea, the evidence of self selection on the basis of productivity is much weaker. In addition, unlike Taiwan, we find no significant productivity changes following entry or exit from the export market that are consistent with learning from exporting. Comparison,of the two countries suggests that in Korea factors other than production efficiency play a more prominent role as determinants of the export decision. JEL Categories: F14, O12, D24