Productivity: More with Less by Better
Available resources are scarce. To sustain our society's income and living standards in a world with ecological and demographic change, we need to make smarter use of them.
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In a nutshell
Nobel Prize winners Paul Samuelson and William Nordhaus state in their classic economics textbook: Economics matters because resources are scarce. Indeed, productivity research is at the very heart of economics as it describes the efficiency with which these scarce resources are transformed into goods and services and, hence, into social wealth. If the consumption of resources is to be reduced, e. g., due to ecological reasons, our society’s present material living standards can only be maintained by productivity growth. The aging of our society and the induced scarcity of labour is a major future challenge. Without productivity growth a solution is hard to imagine. To understand the processes triggering productivity growth, a look at micro data on the level of individual firms or establishments is indispensable.
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Productivity is output in relation to input. While the concept of total factor productivity describes how efficiently labour, machinery, and all combined inputs are used, labour productivity describes value added (Gross Domestic Product, GDP) per worker and measures, in a macroeconomic sense, income per worker.
Productivity Growth on the Slowdown
Surprisingly, despite of massive use of technology and rushing digitisation, advances in productivity have been slowing down during the last decades. Labour productivity growth used to be much higher in the 1960s and 1970s than it is now. For the G7 countries, for example, annual growth rates of GDP per hour worked declined from about 4% in the early 1970s to about 2% in the 1980s and 1990s and then even fell to about 1% after 2010 (see figure 1).

This implies a dramatic loss in potential income: Would the 4% productivity growth have been sustained over the four and a half decades from 1972 to 2017, G7 countries’ GDP per hour would now be unimaginable 2.5 times as high as it actually is. What a potential to, for instance, reduce poverty or to fund research on fundamentals topics as curing cancer or using fusion power!
So why has productivity growth declined dramatically although at the same time we see, for instance, a boom in new digital technologies that can be expected to increase productivity growth? For sure, part of the decline might be spurious and caused by mismeasurement of the contributions of digital technologies. For instance, it is inherently difficult to measure the value of a google search or another video on youtube. That being said, most observers agree that part of the slowdown is real.
Techno-Pessimists and Techno-Optimists
Techno-pessimists say, well, these new technologies are just not as consequential for productivity as, for instance, electrification or combustion engines have been. Techno-optimists argue that it can take many years until productivity effects of new technologies kick in, and it can come in multiple waves. New technology we have now may just be the tools to invent even more consequential innovations in the future.
While this strand of the discussion is concerned with the type of technology invented, others see the problem in that inventions nowadays may diffuse slowly from technological leaders to laggards creating a wedge between few superstar firms and the crowd (Akcigit et al., 2021). Increased market concentration and market power by superstar firms may reduce competitive pressure and the incentives to innovate.
Finally, reduced Schumpeterian business dynamism, i.e. a reduction in firm entry and exit as well as firm growth and decline, reflects a slowdown in the speed with which production factors are recombined to find their most productive match.
While the explanation for and the way out of the productivity puzzle are still unknown, it seems understood that using granular firm level data is the most promising path to find answers.
What are the Origins of Productivity Growth?
Aggregate productivity growth can originate from (i) a more efficient use of available inputs at the firm level as described above or (ii) from an improved allocation of resources between firms.
Higher efficiency at the firm level captures, e.g., the impact of innovations (Acemoglu et al., 2018) or improved firm organisation (management) (Heinz et al., 2020; Müller und Stegmaier, 2017), while improved factor allocation describes the degree of which scarce input factors are re-allocated from inefficient to efficient firms (‘Schumpeterian creative destruction’) (Aghion et al., 2015; Decker et al., 2021).
Most economic processes influence the productivity of existing firms and the growth and the use of resources of these firms and their competitors as well. The accelerated implementation of robotics in German plants (Deng et al., 2020), the foreign trade shocks induced by the rise of the Chinese economy (Bräuer et al., 2019), but also the COVID-19 pandemic, whose consequences are still to evaluate (Müller, 2021) not only effects on productivity and growth of the firms directly affected but at the same time may create new businesses and question existing firms.
While productivity can be measured at the level of aggregated sectors or economies, micro data on the level of individual firms or establishments are indispensable to study firm organisation, technology and innovation diffusion, superstar firms, market power, factor allocation and Schumpeterian business dynamism. The IWH adopts this micro approach within the EU Horizon 2020 project MICROPROD as well as with the CompNet research network.
As “creative destruction” may also negatively affect the persons involved (e. g., in the case of layoffs, Fackler et al., 2021), the IWH analyses the consequences of bankruptcies in its Bankruptcy Research Unit and looks at the implications of creative destruction for the society, e. g., within a project funded by Volkswagen Foundation searching for the economic origins of populism and in the framework of the Institute for Research on Social Cohesion.
Publications on “Productivity”

Import Competition and Firm Productivity: Evidence from German Manufacturing
in: World Economy, forthcoming
Abstract
Abstract We study how different types of import competition affect firm productivity using firm-product data from German manufacturing (2000-2014). Competition from high-income countries causes affected domestic firms to increase their productivity and lower their prices. Oppositely, import competition from low-wage countries does not lead to firm productivity gains. Instead, domestic firms' sales and input usage decline. Our findings confirm the intuition of ladder models that the effect of competition depends on the "closeness" of competitors. They are in line with widespread X-inefficiencies throughout the economy, which firms reduce in response to competition from high-income countries.

Productivity, Place, and Plants
in: Review of Economics and Statistics, forthcoming
Abstract
Why do cities differ so much in productivity? A long literature has sought out systematic sources, such as inherent productivity advantages, market access, agglomeration forces, or sorting. We document that up to three quarters of the measured regional productivity dispersion is spurious, reflecting the “luck of the draw” of finite counts of idiosyncratically heterogeneous plants that happen to operate in a given location. The patterns are even more pronounced for new plants, hold for alternative productivity measures, and broadly extend to European countries. This large role for individual plants suggests a smaller role for places in driving regional differences.

Total Factor Productivity Growth at the Firm-level: The Effects of Capital Account Liberalization
in: Journal of International Economics, forthcoming
Abstract
This study provides firm-level evidence on the effect of capital account liberalization on total factor productivity (TFP) growth. We find that a one standard deviation increase in the capital account openness indicator constructed by Fernández et al. (2016) is significantly associated with a 0.18 standard deviation increase in firms’ TFP growth rates. The productivity-enhancing effects are stronger for sectors with higher external finance dependence and capital-skill complementarity, and are persistent five years after liberalization. Moreover, we show that potential transmission mechanisms include improved financing conditions, greater skilled labor utilization, and technology upgrades. Finally, we document heterogeneous effects across firm size and tradability, and threshold effects with respect to the country's institutional quality.

Cross-country Evidence on the Allocation of COVID-19 Government Subsidies and Consequences for Productivity
in: Journal of the Japanese and International Economies, June 2023
Abstract
We study the consequences of the Covid-19 pandemic and related policy support on productivity. We employ an extensive micro-distributed exercise to access otherwise unavailable individual data on firm performance and government subsidies. Our cross-country evidence for five EU countries shows that the pandemic led to a significant short-term decline in aggregate productivity and the direct support to firms had only a limited positive effect on productivity developments. A thorough comparative analysis of the distribution of employment and overall direct subsidies, considering separately also relative firm-level size of support and the probability of being supported, reveals ambiguous cross-country results related to the firm-level productivity and points to the decisive role of other firm characteristics.

Skill Mismatch and the Costs of Job Displacement
in: IWH Discussion Papers, No. 11, 2023
Abstract
When workers are displaced from their jobs in mass layoffs or firm closures, they experience lasting adverse labor market consequences. We study how these consequences vary with the amount of skill mismatch that workers experience when returning to the labor market. Using novel measures of skill redundancy and skill shortage, we analyze individuals‘ work histories in Germany between 1975 and 2010. We estimate difference-in-differences models, using a sample in which we match displaced workers to statistically similar non-displaced workers. We find that displacements increase the probability of occupational change eleven fold, and that the type of skill mismatch after displacement is strongly associated with the magnitude of post-displacement earnings losses. Whereas skill shortages are associated with relatively quick returns to the counterfactual earnings trajectories that displaced workers would have experienced absent displacement, skill redundancy sets displaced workers on paths with permanently lower earnings.