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on Business Economics |
| By: | Huseyin Gurkan (ESMT European School of Management and Technology); Francis de Véricourt (ESMT European School of Management and Technology) |
| Abstract: | This paper explores how firms that lack expertise in machine learning (ML) can leverage the so-called AI Flywheel effect. This eff ect designates a virtuous cycle by which, as an ML product is adopted and new user data are fed back to the algorithm, the product improves, enabling further adoptions. However, managing this feedback loop is difficult, especially when the algorithm is contracted out. Indeed, the additional data that the AI Flywheel effect generates may change the provider's incentives to improve the algorithm over time. We formalize this problem in a simple two-period moral hazard framework that captures the main dynamics between machine learning, data acquisition, pricing, and contracting. We find that the firm's decisions crucially depend on how the amount of data on which the machine is trained interacts with the provider's effort. If this effort has a more (resp. less) significant impact on accuracy for larger volumes of data, the firm underprices (resp. overprices) the product. Interestingly, these distortions sometimes improve social welfare, which accounts for the customer surplus and profits of both the firm and provider. Further, the interaction between incentive issues and the positive externalities of the AI Flywheel effect have important implications for the firm's data collection strategy. In particular, the firm can boost its profit by increasing the product's capacity to acquire usage data only up to a certain level. If the product collects too much data per user, the firm's profit may actually decrease. As a result, the firm should consider reducing its product's data acquisition capacity when its initial dataset to train the algorithm is large enough. |
| Keywords: | Data, machine learning, data product, pricing, incentives, contracting |
| Date: | 2020–03–03 |
| URL: | http://d.repec.org/n?u=RePEc:esm:wpaper:esmt-20-01_r1&r=all |
| By: | Ichiro Iwasaki; Evžen Kocenda; Yoshisada Shida |
| Abstract: | In this paper, we traced the survival status of 94,401 small businesses in 17 European emerging markets from 2007–2017 and empirically examined the determinants of their survival, focusing on institutional quality and financial development. We found that institutional quality and the level of financial development exhibit statistically significant and economically meaningful impacts on the survival probability of the SMEs being researched. The evidence holds even when we control for a set of firm-level characteristics such as ownership structure, financial performance, firm size, and age. The findings are also uniform across industries and country groups and robust beyond the difference in assumption of hazard distribution, firm size, region, and time period. |
| Keywords: | small business, institutions, financial development, survival analysis, European emerging markets |
| JEL: | C14 D02 D22 G33 M21 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_8641&r=all |
| By: | Hassan Afrouzi; Andres Drenik; Ryan Kim |
| Abstract: | How are a firm’s size and market power related to one another? Combining micro-data about producers and consumers, we document that while firms mainly grow by selling to more customers, their markups are only associated with their average sales per customer. To study the macroeconomic implications of these facts, we develop a model of firm dynamics with endogenous customer acquisition and variable markups. Relative to a model without customer acquisition, our model generates higher concentration at the top, but a lower aggregate markup. Our quantitative analysis reveals large welfare and efficiency losses due to (mis)allocation of customers across firms. By increasing market concentration among the most productive firms, the efficient allocation achieves 11% higher aggregate productivity and 15% higher output. |
| Keywords: | customer acquisition, misallocation, concentration, markups |
| JEL: | D24 D42 D61 E22 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_8633&r=all |
| By: | Leland Crane; Ryan Decker; Aaron Flaaen; Adrian Hamins-Puertolas; Christopher J. Kurz |
| Abstract: | Given lags in official data releases, economists have studied "alternative data" measures of business exit resulting from the COVID-19 pandemic. Such measures are difficult to understand without historical context, so we review official data on business exit in recent decades. Business exit is common in the U.S., with about 7.5 percent of firms exiting annually in recent years, and is countercyclical (particularly recently). Both the high level and the cyclicality of exit are driven by very small firms. We explore a range of alternative measures and indicators of business exit, including novel measures based on payroll events and phone-tracking data, and find tentative evidence that exit has been elevated during 2020. Evidence is somewhat mixed, however, and exiting businesses do not appear to represent a large share of U.S. employment. |
| Keywords: | Business cycles; Business exit; Firm dynamics; Job destruction; Nontraditional data |
| JEL: | E32 C55 C81 D22 |
| Date: | 2020–10–22 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:2020-89&r=all |
| By: | Victoria Gregory |
| Abstract: | This paper demonstrates that heterogeneity in firms’ promotion of human capital accumulation is an important determinant of life-cycle earnings inequality. I use administrative micro data from Germany to show that different establishments offer systematically different earnings growth rates for their workers. This observation suggests that that the increase in inequality over the life cycle reflects not only inherent worker variation, but also differences in the firms that workers happen to match with over their lifetimes. To quantify this channel, I develop a life-cycle search model with heterogeneous workers and firms. In the model, a worker’s earnings can grow through both human capital accumulation and labor market competition channels. Human capital growth depends on both the worker’s ability and the firm’s learning environment. I find that heterogeneity in firm learning environments account for 40% of the increase in cross-sectional earnings variance over the life cycle, and that this mechanism is especially important for young workers. I then show that differences in labor market histories partially shape the worker-specific income profiles estimated by reduced-form statistical earnings processes. Finally, because young workers do not fully internalize the benefits of matching to high-growth firms, changes to the structure of unemployment insurance policies can incentivize these workers to search for better matches. |
| Keywords: | human capital; earnings dynamics; firms; inequality; search; labor markets |
| JEL: | E24 J24 |
| Date: | 2020–08–14 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedlwp:88971&r=all |
| By: | Pradhana, Made Bagoes |
| Abstract: | Firm Performance (Kinerja Perusahaan) |
| Date: | 2020–10–03 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:ckfp6&r=all |
| By: | Elert, Niklas (Research Institute of Industrial Economics (IFN)); Stenkula, Mikael (Research Institute of Industrial Economics (IFN)) |
| Abstract: | Researchers increasingly recognize that entrepreneurial employees, intrapreneurs, play a critical role in innovation. As with regular entrepreneurship, however, the value of intrapreneurial activity depends on the firm-specific and societal reward structures that intrapreneurs face. Ideally, these rules of the game are such that they reward intrapreneurship that is beneficial for the firm and the economy. When this is not the case, intrapreneurship can be beneficial for the firm but not for society, damaging for the firm yet beneficial for society, or downright destructive. We offer a taxonomy describing how society’s rules and firm rules interact to produce different intrapreneurial outcomes. |
| Keywords: | Intrapreneurship; Entrepreneurship; Entrepreneurial behavior |
| JEL: | D02 J24 L26 M14 O17 O31 |
| Date: | 2020–10–26 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:iuiwop:1367&r=all |
| By: | Kang, Natasha; Marmer, Vadim |
| Abstract: | Recurrent boom-and-bust cycles are a salient feature of economic and finan- cial history. Cycles found in the data are stochastic, often highly persistent, and span substantial fractions of the sample size. We refer to such cycles as “long†. In this paper, we develop a novel approach to modeling cyclical behavior specifically designed to capture long cycles. We show that existing inferential procedures may produce misleading results in the presence of long cycles, and propose a new econometric procedure for the inference on the cycle length. Our procedure is asymptotically valid regardless of the cycle length. We apply our methodology to a set of macroeconomic and financial variables for the U.S. We find evidence of long stochastic cycles in the standard business cycle variables, as well as in credit and house prices. However, we rule out the presence of stochastic cycles in asset market data. Moreover, according to our result, financial cycles as characterized by credit and house prices tend to be twice as long as business cycles. |
| Keywords: | Stochastic cycles, autoregressive processes, local-to-unity asymptotics, confi- dence sets, business cycle, financial cycle |
| JEL: | C12 C22 C5 E32 E44 |
| Date: | 2020–10–25 |
| URL: | http://d.repec.org/n?u=RePEc:ubc:bricol:vadim_marmer-2020-3&r=all |
| By: | Jing Hang; Pravin Krishna; Heiwai Tang |
| Abstract: | This paper develops a framework for studying the macroeconomic costs of resource misallocation. The framework enables the assessment of the conditions under which the existing estimates in the misallocation literature, which are largely based on a value-added production structure and ignore inter-sectoral linkages, provide an unbiased estimate of misallocation costs in relation to a more general setting, in which production of gross output relies upon input-output linkages across sectors. We show that in the absence of intermediate input distortions, the two approaches are isomorphic and will yield the same estimated aggregate productivity loss. When firm-specific intermediate input distortions are present, however, the value-added model produces biased estimates of TFP losses due to both model misspecification and incorrect inferences of firms' productivity and distortions. Using Chinese and Indian enterprise data, we find quantitatively similar TFP losses from resource misallocation for China, regardless of the model used, while for India, we infer significantly larger TFP losses under the gross output model. |
| JEL: | E1 E23 L16 O11 O4 |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27983&r=all |