In economic theory, entrepreneurship is perceived as a driving force behind the process of creative destruction by introducing innovation to the market, crowding out inefficient businesses, and paving the way for economic growth. One central channel through which entrepreneurial activity can be realized is the founding a new firm (Carree & Thurik, 2003). Numerous empirical studies have investigated the causes of firm entry, the subsequent fate of these young businesses, and their impact on the economy (Geroski, 1995; Wagner, 2006). When assessing the importance of start-ups for economic development, their role in the creation and destruction of jobs is a key component. This thesis argues that start-ups’ role as employers should be evaluated not only by the quantity of jobs they create, but also by the quality of these jobs. If new firms differ from incumbents in terms of hiring patterns or employment conditions, this could have serious and long-lasting implications for the careers and personal lives of their employees. Against this background, the four essays of this thesis present new evidence on the hiring behavior of newly founded establishments, as well as on remuneration and employment prospects of workers joining a start-up.

This paper investigates whether and how economic policy uncertainty affects corporate debt maturity. Using a large firm-level dataset for four European countries, we find that an increase in economic policy uncertainty is significantly associated with a shortened debt maturity. Moreover, the impacts are stronger for innovation-intensive firms. We use firms’ flexibility in changing debt maturity and the deviation to leverage target to gauge the causal relationship, and identify the reduced investment and steepened term structure as the transmission mechanisms.

This paper studies whether and how banks’ technological innovations affect the bank lending channel of monetary policy transmission. We first provide a theoretical model in which banks’ technological innovation relaxes firms’ earning-based borrowing constraints and thereby enlarges the response of banks’ lending to monetary policy changes. To test the empirical implications, we construct a patent-based measurement of bank-level technological innovation, which can specify the nature of technology and tell whether it is related to the bank’s lending business. We find that lending-related innovations significantly strengthen the transmission of the bank lending channel.

In this paper, we examine the impact of female Chief Technology Officers (CTOs) on corporate innovation. We find that firms with female CTOs are more innovative (as captured by both patent counts and patent citations) than firms with male CTOs. This effect is more pronounced for firms with a stronger innovation-supportive culture, firms with female CEOs, and when female CTOs are more powerful. Using mediation analyses, we further validate that female CTOs’ transformational leadership style is a plausible mechanism through which they affect innovation positively.

Asset prices are a valuable source of information about financial market participants' expectations about key macroeconomic variables. However, the presence of time-varying risk premia requires an adjustment of market prices to obtain the market's rational assessment of future price and policy developments. This paper reviews empirical approaches for recovering market-based expectations. It starts by laying out the two canonical modeling frameworks that form the backbone for estimating risk premia and highlights the proliferation of risk pricing factors that result in a wide range of different asset-price-based expectation measures. It then describes a key methodological innovation to evaluate the empirical plausibility of risk premium estimates and to identify the most accurate market-based expectation measure. The usefulness of this general approach is illustrated for price expectations in the global oil market. Then, the paper provides an overview of the body of empirical evidence for monetary policy and inflation expectations with a special emphasis on market-specific characteristics that complicate the quest for the best possible market-based expectation measure. Finally, it discusses a number of economic applications where market expectations play a key role for evaluating economic models, guiding policy analysis, and deriving shock measures.

My dissertation consists of three studies, all viewing aggregate productivity as driven by the individual decisions of firms and the inventors that work for them. I use microeconometric analysis to study why firms innovate and economic theory to link these decisions to macroeconomic outcomes. The first paper in this dissertation studies how German manufacturing firms adjust their productivity in response to an increase in competition from foreign markets. German firms only increase their productivity if their new competitors come from other industrialized economies. This productivity increase is not driven by innovation. Instead, firms cut input expenses and prices while maintaining their output. The second paper traces the matching decisions of firms and inventors on the labor markets of developed economies. It adapts empirical techniques used in labor economics to this special segment of the labor market and shows that assortative matching has been increasing from 1974 to 2012: High quality inventors go to high quality firms more often than was the case in previous decades. This cannot be explained by changes in the patent invention function: The productivity of a match between a firm and an inventor of constant quality remains roughly unchanged. The third paper develops an endogenous growth model with inventor labor markets and two types of innovation: disruptive inventions that change the underlying technology of firms’ products and incremental improvements over existing products. Firms acquire expertise in certain technologies by hiring the inventors who are experts in these fields. This gives them a strong incentive to prevent disruptive inventions: If the underlying technology changes, their investment in these inventors becomes worthless. Large firms inhibit aggregate growth by poaching inventors from firms engaged in disruptive innovation.

Purpose:

This paper aims to examine the presence of an executive with customer experience (ECE) in a supplier firm’s top management team (TMT). The role of ECE presence remains understudied in the marketing literature. This study attempts to examine the relationship between ECE presence and firm performance.

Design/methodology/approach:

This paper draws on the resource-based view of the firm and adopts a panel firm fixed effects estimator to test the proposed hypotheses. The empirical analysis uses a sample of 1,974 firm-year observations with 489 unique supplier firms. Selection-induced endogeneity is mitigated through the Heckman procedure.

Findings:

ECE presence improves firm performance. Additionally, firms benefit less from ECE presence if a board member with customer experience (BCE) is also present, if a chief executive officer commands a higher pay slice (compared to other executives), and if a TMT is more functionally diversified. However, ECE presence is particularly beneficial if the overall economy is in contraction. Comparing the functional positions held by ECEs reveals that ECE in the marketing function (as a chief marketing officer) offers the largest benefit to an average supplier firm. ECE presence is also associated with other firm outcomes (e.g. bankruptcy odds, innovation and customer orientation).

Measuring innovation is challenging both for researchers and for national statisticians, and it is increasingly important in light of the ongoing digital revolution. National accounts and many other economic statistics were designed before the emergence of the digital economy and the growing importance of intangible capital. They do not yet fully capture the wide range of innovative activity that is observed in modern economies.
This volume examines how to measure innovation, track its effects on economic activity and prices, and understand how it has changed the structure of production processes, labor markets, and organizational form and operation in business. The contributors explore new approaches to, and data sources for, measurement—such as collecting data for a particular innovation as opposed to a firm, and the use of trademarks for tracking innovation. They also consider the connections between university-based R&D and business startups, and the potential impacts of innovation on income distribution.
The research suggests potential strategies for expanding current measurement frameworks to better capture innovative activity, such as more detailed tracking of global value chains to identify innovation across time and space, and expanding the measurement of the GDP impacts of innovation in fields such as consumer content delivery and cloud computing.

Measuring innovation is challenging both for researchers and for national statisticians, and it is increasingly important in light of the ongoing digital revolution. National accounts and many other economic statistics were designed before the emergence of the digital economy and the growing importance of intangible capital. They do not yet fully capture the wide range of innovative activity that is observed in modern economies. This volume examines how to measure innovation, track its effects on economic activity and prices, and understand how it has changed the structure of production processes, labor markets, and organizational form and operation in business. The contributors explore new approaches to, and data sources for, measurement—such as collecting data for a particular innovation as opposed to a firm, and the use of trademarks for tracking innovation. They also consider the connections between university-based R&D and business startups, and the potential impacts of innovation on income distribution. The research suggests potential strategies for expanding current measurement frameworks to better capture innovative activity, such as more detailed tracking of global value chains to identify innovation across time and space, and expanding the measurement of the GDP impacts of innovation in fields such as consumer content delivery and cloud computing.