Artificial Intelligence (AI) is often regarded as the next general-purpose technology with a rapid, penetrating, and far-reaching use over a broad number of industrial sectors. The main feature of new general-purpose technology is to enable new ways of production that may increase productivity. However, to date, only a few studies have investigated the likely productivity effects of AI at the firm-level, presumably due to limited data availability. We exploit unique survey data on firms’ adoption of AI technology and estimate its productivity effects with a sample of German firms. We employ both a cross-sectional dataset and a panel database. To address the potential endogeneity of AI adoption, we also implement IV estimators. We find positive and significant associations between the use of AI and firm productivity. This finding holds for different measures of AI usage, i.e., an indicator variable of AI adoption, and the intensity with which firms use AI methods in their business processes.

This paper analyses the link between the use of Artificial Intelligence (AI) and innovation performance in firms. Based on firm-level data from the German part of the Community Innovation Survey (CIS) 2018, we examine the role of different AI methods and application areas in innovation. The results show that 5.8% of firms in Germany were actively using AI in their business operations or products and services in 2019. We find that the use of AI is associated with annual sales with world-first product innovations in these firms of About €16 billion (i.e. 18% of total annual sales of world-first innovations). In addition, AI technologies have been used in process innovation that contributed to About 6% of total annual cost savings of the German business sector. Firms that apply AI broadly (using different methods for different applications areas) and that have already several years of experience in using AI obtain significantly higher innovation results. These positive findings on the role of AI for innovation have to be interpreted with caution as they refer to a specific country (Germany) in a situation where AI started to diffuse rapidly.

This paper examines whether personality influences the allocation of resources within households. To do so, I model households as couples that make Pareto-efficient allocations and divide resources according to a distribution function. Using a sample of Dutch couples from the LISS survey with detailed information on consumption, labor supply, and personality traits at the individual level, I find that personality affects intrahousehold allocations through two channels. Firstly, the level of these traits act as preference factors that shape individual tastes for consumed goods and leisure time. Secondly, by testing distribution factor proportionality and the exclusion restriction of a conditional demand system, I observe that differences in personality between spouses act as distribution factors. Specifically, these differences in personality impact the allocation of resources by affecting the bargaining process within households. For example, women who are relatively more conscientious and engage more cognitively than their male partners receive a larger share of intrafamily resources.

Artificial Intelligence (AI) is considered to be the next general-purpose technology, with the potential of performing tasks commonly requiring human capabilities. While it is commonly feared that AI replaces labor and disrupts jobs, we instead investigate the potential of AI for overcoming increasingly alarming skills shortages in firms. We exploit unique German survey data from the Mannheim Innovation Panel on both the adoption of AI and the extent to which firms experience scarcity of skills. We measure skills shortage by the number of job vacancies that could not be filled as planned by firms, distinguishing among different types of skills. To account for the potential endogeneity of skills shortage, we also implement instrumental variable estimators. Overall, we find a positive and significant effect of skills shortage on AI adoption, the breadth of AI methods, and the breadth of areas of application of AI. In addition, we find evidence that scarcity of labor with academic education relates to firms exploring and adopting AI.

This paper studies the influence of parental personality on child development throughout the life cycle. Leveraging detailed individual-level data from the PSID and its Child Development and Wellbeing Supplements, we show significant heterogeneity concerning parental personality, children’s skills, accepted wages, and time-use decisions. Firstly, we observe that personality traits impact parents’ wages and time allocation between market work and child-rearing. Secondly, our result suggests systematic heterogeneity in the relative input productivity (or quality) of childcare time across parents with different personality levels. To provide a rationale for these observed patterns, we identify and estimate a life-cycle model that incorporates parental personality and considers household decisions with an endogenous technology for a child’s cognitive and non-cognitive skill formation. We employ the estimated model to determine the optimal targeting of simulated interventions tailored to children from parents with diverse personality traits. Our results reveal the limitations of one-size-fits-all parenting support and child welfare policies that do not acknowledge the diverse impacts of parental personality on child development.

We develop an empirical framework to analyze the dynamic effect of personality traits in marriage market patterns and intrahousehold decisions. We exploit detailed information at the individual level from the HILDA survey about consumption, labor supply, time use, and personality traits (as measured by the Big Five). First, we document that personality types are related to marital and divorce patterns, time allocated to both market labor and non-market labor activities, and the evolution of earnings. Next, to rationalize these empirical facts, we build a life-cycle model that integrates endogenous household formation and collective household choices under limited commitment. Our framework allows personality to affect both wages and individual preferences. In the latter, personality traits enter indirectly through the intrahousehold production of a public good and the utility of marriage (match quality). We use the estimates of our model to conduct policy counterfactuals associated with sorting in the marriage market and intrahousehold behavior.