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Liquidity derivatives
(2022)
It is well established that investors price market liquidity risk. Yet, there exists no financial claim contingent on liquidity. We propose a contract to hedge uncertainty over future transaction costs, detailing potential buyers and sellers. Introducing liquidity derivatives in Brunnermeier and Pedersen (2009) improves financial stability by mitigating liquidity spirals. We simulate liquidity option prices for a panel of NYSE stocks spanning 2000 to 2020 by fitting a stochastic process to their bid-ask spreads. These contracts reduce the exposure to liquidity factors. Their prices provide a novel illiquidity measure refllecting cross-sectional commonalities. Finally, stock returns significantly spread along simulated prices.
Peer effects can lead to better financial outcomes or help propagate financial mistakes across social networks. Using unique data on peer relationships and portfolio composition, we show considerable overlap in investment portfolios when an investor recommends their brokerage to a peer. We argue that this is strong evidence of peer effects and show that peer effects lead to better portfolio quality. Peers become more likely to invest in funds when their recommenders also invest, improving portfolio diversification compared to the average investor and various placebo counterfactuals. Our evidence suggests that social networks can provide good advice in settings where individuals are personally connected.
What are the aggregate and distributional consequences of the relationship be-tween an individual’s social network and financial decisions? Motivated by several well-documented facts about the influence of social connections on financial decisions, we build and calibrate a model of stock market participation with a social network that emphasizes the interplay between connectivity and network structure. Since connections to informed agents help spread information, there is a pivotal role for factors that determine sorting among agents. An increase in the average number of connections raises the average participation rate, mostly due to richer agents. A higher degree of sorting benefits richer agents by creating clusters where information spreads more efficiently. We show empirical evidence consistent with the importance of connectivity and sorting. We discuss several new avenues for future research into the aggregate impact of peer effects in finance.
Chiromantie (Handlesekunst) : Erfurt, Universitätsbibliothek, Dep. Erf. CA. 4° 21, f. 127v-131r
(2006)
Die Kunst, aus der Hand zu lesen, konnte im Mittelalter als ein Zweig der Physiognomie aufgefasst werden, der Wissenschaft von der Kunst, die Wesensart eines Menschen aus seiner leiblichen Erscheinung herauszulesen. Teils stand die Wissenschaftlichkeit der Chiromantik aber auch in Frage: wenn nämlich dem Menschen über seinen Charakter hinaus auch seine Zukunft aus der Hand gelesen werden sollte. So lehnte der 1439 in Padua zum Doktor der Freien Künste und der Medizin promovierte Johannes Hartlieb 1456 in seinem ,Buch aller verbotenen Künste' einerseits die Chiromantik als sünd, verpoten und ain rechter ungelaub ab, obwohl andererseits ein Ende der siebziger Jahre aufgelegtes Blockbuch eben Hartlieb als Verfasser einer deutschen Chiromantie auftreten lässt, die er schon 1448 der Gemahlin Herzog Albrechts 111. von Bayern gewidmet haben soll.
Die spätantiken ,Disticha Catonis', von einem unbekannten Autor im 3./4. Jahrhundert verfasst, dienten seit karolingischer Zeit dem Unterricht in der gramatica. Dort hielten sie dem Lateinschüler sprachliches Anschauungsmaterial ebenso bereit wie, das war dem mittelalterlichen Trivialunterricht nicht minder wichtig, elementare Verhaltenslehre in leicht memorierbarer Form. So unterweisen die circa 140 Hexameterdistichen aus einer vulgärstoizistischen Grundhaltung heraus etwa im rechten Umgang mit Besitz, mit den eigenen Affekten, mit Leid und Tod, oder wie man sich Fremden, Freunden oder der eigenen Frau gegenüber verhalten soll. Der Bestand der Distichen wurde bereits in mehreren vorkarolingischen Redaktion auf vier Bücher verteilt und um Prosasentenzen (breves sententiae) vor Buch I und metrische Vorreden zu Buch II-IV erweitert. Eine das Werk eröffnende, knappe Prosavorrede (praefatio) ist einem sorgenden Vater in den Mund gelegt, der die Lehren seinem geliebten Sohn ans Herz legt.
Financial markets are to a very large extent influenced by the advent of information. Such disclosures, however, do not only contain information about fundamentals underlying the markets, but they also serve as a focal point for the beliefs of market participants. This dual role of information gains further importance for explaining the development of asset valuations when taking into account that information may be perceived individually (private information), or may be commonly shared by all traders (public information). This study investigates into the recently developed theoretical structures explaining the operating mechanism of the two types of information and emphasizes the empirical testability and differentiation between the role of private and public information. Concluding from a survey of experimental studies and own econometric analyses, it is argued that most often public information dominates private information. This finding justifies central bankers´ unease when disseminating news to the markets and argues against the recent trend of demanding full transparency both for financial institutions and financial markets themselves.
Small and medium-sized firms typically obtain capital via bank financing. They often rely on a mixture of relationship and arm’s-length banking. This paper explores the reasons for the dominance of heterogeneous multiple banking systems. We show that the incidence of inefficient credit termination and subsequent firm liquidation is contingent on the borrower’s quality and on the relationship bank’s information precision. Generally, heterogeneous multiple banking leads to fewer inefficient credit decisions than monopoly relationship lending or homogeneous multiple banking, provided that the relationship bank’s fraction of total firm debt is not too large.
Small and medium-sized firms typically obtain capital via bank financing. They often rely on a mixture of relationship and arm’s-length banking. This paper explores the reasons for the dominance of heterogeneous multiple banking systems. We show that the incidence of inefficient credit termination and subsequent firm liquidation is contingent on the borrower’s quality and on the relationship bank’s information precision. Generally, heterogeneous multiple banking leads to fewer inefficient credit decisions than monopoly relationship lending or homogeneous multiple banking, provided that the relationship bank’s fraction of total firm debt is not too large.
Doing safe by doing good : ESG investing and corporate social responsibility in the U.S. and Europe
(2019)
This paper examines the profitability of investing according to environmental, social and governance (ESG) criteria in the U.S. and Europe. Based on data from 2003 to 2017, we show that a portfolio long in stocks with the highest ESG scores and short in those with the lowest scores yields a significantly negative abnormal return. Interestingly, this is caused by the strong positive return of firms with the lowest ESG activity. As we find that increasing ESG scores reduce firm risk (particularly downside risk), this hints at an insurance-like character of corporate social responsibility: Firms with low ESG activity need to offer a corresponding risk premium. The perception of ESG as an insurance can be shown to be stronger in more volatile capital markets for U.S. firms, but not for European firms. Socially responsible investment may therefore be of varying attractiveness in different market phases.
Open-end real estate funds are of particular importance in the German bank-dominated financial system. However, recently the German open-end fund industry came under severe distress which triggered a broad discussion of required regulatory interventions. This paper gives a detailed description of the institutional structure of these funds and of the events that led to the crisis. Furthermore, it applies recent banking theory to openend real estate funds in order to understand why the open-end fund structure was so prevalent in Germany. Based on these theoretical insights we evaluate the various policy recommendations that have been raised.
Open-end real estate funds are of particular importance in the German bankdominated financial system. However, recently the German open-end fund industry came under severe distress which triggered a broad discussion of required regulatory interventions. This paper gives a detailed description of the institutional structure of these funds and of the events that led to the crisis. Furthermore, it applies recent banking theory to open-end real estate funds in order to understand why the open-end fund structure was so prevalent in Germany. Based on these theoretical insights we evaluate the various policy recommendation that have been raised.
This paper examines the effect of imperfect labor market competition on the efficiency of compensation schemes in a setting with moral hazard, private information and risk-averse agents. Two vertically differentiated firrms compete for agents by offering contracts with fixed and variable payments. Vertical differentiation between firms leads to endogenous, type-dependent exit options for agents. In contrast to screening models with perfect competition, we find that existence of equilibria does not depend on whether the least-cost separating allocation is interim efficient. Rather, vertical differentiation allows the inferior firm to offer (cross-)subsidizing fixed payments even above the interim efficient level. We further show that the efficiency of variable pay depends on the degree of competition for agents: For small degrees of competition, low-ability agents are under-incentivized and exert too little effort. For large degrees of competition, high-ability agents are over-incentivized and bear too much risk. For intermediate degrees of competition, however, contracts are second-best despite private information.
This paper provides new insights into the nature of loan securitization. We analyze the use of collateralized loan obligation (CLO) transactions by European banks from 1997 to 2004 andtry to identify the influence that various firm-specific and macroeconomic factors may have on an institution's securitization decision. We find that not only regulatory capital arbitrage under Basel I has been driving the market. Rather, our results suggest that loan securitization is an appropriate funding tool for banks with high risk and low liquidity. It may also have been used by commercial banks to indirectly access investment-bank activities and the associated gains.
This study examines the role of actual and perceived financial sophistication (i.e., financial literacy and confidence) for individuals' wealth accumulation. Using survey data from the German SAVE initiative, we find strong gender- and education-related differences in the distribution of the two variables and their effects on wealth: As financial literacy rises in formal education, whereas confidence increases in education for men but decreases for women, we observe that women become strongly underconfident with higher education, while men remain overconfident.Regarding wealth accumulation, we show that financial literacy has a positive effect that is stronger for women than for men and that is increasing (decreasing) in education for women (men). Confidence, however, supports only highly-educated men's wealth. When considering different channels for wealth accumulation, we observe that financial literacy is more important for current financial market participation, whereas confidence is more strongly associated with future-oriented financial planning. Overall, we demonstrate that highly-educated men's wealth levels benefit from their overconfidence via all financial decisions considered, but highly-educated women's financial planning suffers from their underconfidence. This may impair their wealth levels in old age.
We analyze the market reaction to the sentiment of the CEO speech at the Annual General Meeting (AGM). As the AGM is typically preceded by several information disclosures, the CEO speech may be expected to contribute only marginally to investors’ decision-making. Surprisingly, however, we observe from the transcripts of 338 CEO speeches of German corporates between 2008 and 2016 that their sentiment is significantly related to abnormal stock returns and trading volumes following the AGM. Using a novel business-specific German dictionary based on Loughran and McDonald (2011), we find a negative association of the post-AGM returns with the speeches’ negativity and a positive association with the speeches’ relative positivity (i.e. positivity relative to negativity). Relative positivity moreover corresponds with a lower trading volume in a short time window surrounding the AGM. Investors hence seem to perceive the sentiment of CEO speeches at AGMs as a valuable indicator of future firm performance.
We examine firms’ simultaneous choice of investment, debt financing and liquidity in a large sample of US corporates between 1980 and 2014. We partition the sample according to the firms’ financial constraints and their needs to hedge against future shortfalls in operating income. In contrast to earlier work, our joint estimation approach shows that cash flows affect the corporate decisions of unconstrained firms more strongly than those of constrained firms. Investment-cash flow sensitivities are particularly intense for unconstrained firms with high hedging needs. Investment opportunities (as proxied by Q), however, play a larger role for constrained firms with the effects being strongest in case of low hedging needs. Interestingly, constrained firms with low hedging needs are found to employ more debt to finance their investment opportunities and build up significant cash holdings at the same time. Our results hence indicate overinvestment behavior for unconstrained firms but no underinvestment for constrained firms if they have low hedging needs.
In this paper, we propose a model of credit rating agencies using the global games framework to incorporate information and coordination problems. We introduce a refined utility function of a credit rating agency that, additional to reputation maximization, also embeds aspects of competition and feedback effects of the rating on the rated firms. Apart from hinting at explanations for several hypotheses with regard to agencies' optimal rating assessments, our model suggests that the existence of rating agencies may decrease the incidence of multiple equilibria. If investors have discretionary power over the precision of their private information, we can prove that public rating announcements and private information collection are complements rather than substitutes in order to secure uniqueness of equilibrium. In this respect, rating agencies may spark off a virtuous circle that increases the efficiency of the market outcome.
This paper studies the use of performance pricing (PP) provisions in debt contracts and compares accounting-based with rating-based pricing designs. We find that rating-based provisions are used by volatile-growth borrowers and allow for stronger spread increases over the credit period. Accounting-based provisions are employed by opaque-growth borrowers and stipulate stronger spread reductions. Further, a higher spread-increase potential in rating-based contracts lowers the spread at the loan’s inception and improves the borrower’s performance later on. In contrast, a higher spread-decrease potential in accounting-based contracts lowers the initial spread and raises the borrower’s leverage afterwards. The evidence indicates that rating-based contracts are indeed employed for different reasons than accounting-based contracts: the former to signal a borrower’s quality, the latter to mitigate investment inefficiencies.
We examine how a firms' investment behavior affects the investment of a neighboring firm. Economic theory yields ambiguous predictions regarding the direction of firm peer effects and consistent with earlier work, we find that firms display similar investment behavior within an area using OLS analysis. Exploiting time-variation in the rise of U.S. states' corporate income taxes and utilizing heterogeneity in firms' exposure to increases in corporate income tax rates, we identify the causal impact of local firms' investments. Using this as an instrumental variable in a 2SLS estimation, we find that an increases in local firms' investment reduces the investment of a local peer firm. This effect is more pronounced if local competition among firms is stronger and supports theories that firm investments are strategic substitutes due to competition.
In the ‘age of transnationalization’, spatial mobility is highly valued as a resource and accordingly ‘sedentariness’ is often symbolically devalued. Migration between Poland and Germany (mainly from Poland to Germany) has a century-long tradition. Not only has it yielded the emergence of a dense transnational social space, but is also considered as a re-enactor of cultural traits and symbolic meanings. Spatial mobility is tied to notions of social mobility and to projects of life-making. Since legal restrictions for Polish migrants seeking to work and settle in Germany have vanished, the quest for ‘normalcy’ has enhanced and pressures towards even more migration have increased. I argue that symbolic meanings of mobility are decisive for hierarchies in transnational social spaces. I have put main emphasize on families’ practices of caring for and caring about each other: the first being more a physical or material activity, while the latter is a more symbolic and emotional one. The interviews reveal that people draw multiple differentiations between migrant populations in terms of their migration reasons as well as between the mobile and the immobile. Those differentiations are embedded in the distinct feature of the transnational social space between Poland and Germany with assumed differences in terms of ‘modernity’. At the end the symbolic meanings of mobility also help explain the puzzle of why the emigration rates from Poland are constantly high, although Poland is a comparatively wealthy country.
Dieser Beitrag ist ein Besprechungsaufsatz zu Beatrice Brunhöbers 2010 erschienener Dissertation Die Erfindung „demokratischer Repräsentation“ in den Federalist Papers (Mohr Siebeck, Tübingen: Grundlagen der Rechtswissenschaft, Bd. 14), in der Brunhöber die innovative – und auch die Verfassungsentwicklung andernorts prägende – Kraft der Verbindung von Demokratie, politischer Repräsentation und Föderalismusidee durch die amerikanischen Verfassungsväter herausarbeitet. Auf der Basis von Brunhöbers Untersuchung geht es insbesondere darum, wie sich das von Hamilton, Madison und Jay entworfene ‚alte‘ Konzept zur Gestaltung eines starken Gemeinwesens (eingeschlossen das vertrauensbildende Prinzip der Gewaltenteilung) für einen integrativen Umgang mit den ‚modernen‘ Gegebenheiten pluralistischer Gesellschaften nutzbar machen läßt, im Blick die Gesamtheit (und Vielfalt) des Staatsvolkes als Geltungsfundament legitimer Herrschaft. Im Hintergrund steht die Frage nach Möglichkeiten zur Nutzbarmachung historischer Vergewisserungen für heutige Debatten überhaupt.
Die folgende Studie steht in Verbindung mit einer intersprachlichen Untersuchung zu der Dimension des sprachlichen Erfassens von Gegenständen im Rahmen des Kölner Projekts für Universalienforschung und Typologie (UNITYP). Im ersten Kapitel werden die zugrundeliegenden theoretischen Begriffe der sprachlichen Universalien und Typologie sowie die Dimension des Erfassens von Gegenständen kurz erörtert, um die Ziele dieser Arbeit in Beziehung zum Forschungsplan des UNITYPs zu setzen. Im zweiten Kapitel wird das Phänomen klassifikatorischer Verben zunächst definiert, und dann werden Systeme klassifikatorischer Verben in ausgewählten Einzelsprachen beschrieben. Abschließend wird der Versuch gemacht, zu zeigen, inwieweit die für eine Einzelsprache beschriebene Erscheinung ein typologisches Charakteristikum der betreffenden Sprachfamilie bzw. Sprachgruppe ist, um damit die Verbreitung von klassifikatorischen Verben in nordamerikanischen Indianersprachen vorläufig abzustecken. Im dritten Kapitel werden Verallgemeinerungen aus den im zweiten Kapitel vorgelegten Daten gezogen, um eine vorläufige typologische Beschreibung der Erscheinung "klassifikatorische Verben" zu erzielen und somit ihre Stellung in der Dimension des Erfassens von Gegenständen sowie in einer konzept-orientierten Typologie zu charakterisieren.
Library Catalog
(2000)
Public employees in many developing economies earn much higher wages than similar privatesector workers. These wage premia may reflect an efficient return to effort or unobserved skills, or an inefficient rent causing labor misallocation. To distinguish these explanations, we exploit the Kenyan government’s algorithm for hiring eighteen-thousand new teachers in 2010 in a regression discontinuity design. Fuzzy regression discontinuity estimates yield a civil-service wage premium of over 100 percent (not attributable to observed or unobserved skills), but no effect on motivation, suggesting rent-sharing as the most plausible explanation for the wage premium.
From 1963 through 2015, idiosyncratic risk (IR) is high when market risk (MR) is high. We show that the positive relation between IR and MR is highly stable through time and is robust across exchanges, firm size, liquidity, and market-to-book groupings. Though stock liquidity affects the strength of the relation, the relation is strong for the most liquid stocks. The relation has roots in fundamentals as higher market risk predicts greater idiosyncratic earnings volatility and as firm characteristics related to the ability of firms to adjust to higher uncertainty help explain the strength of the relation. Consistent with the view that growth options provide a hedge against macroeconomic uncertainty, we find evidence that the relation is weaker for firms with more growth options.
This paper aims at an improved understanding of the relationship between monetary policy and racial inequality. We investigate the distributional effects of monetary policy in a unified framework, linking monetary policy shocks both to earnings and wealth differentials between black and white households. Specifically, we show that, although a more accommodative monetary policy increases employment of black households more than white households, the overall effects are small. At the same time, an accommodative monetary policy shock exacerbates the wealth difference between black and white households, because black households own less financial assets that appreciate in value. Over multi-year time horizons, the employment effects are substantially smaller than the countervailing portfolio effects. We conclude that there is little reason to think that accommodative monetary policy plays a significant role in reducing racial inequities in the way often discussed. On the contrary, it may well accentuate inequalities for extended periods.
This paper investigates the financial contracting behavior of German venture capitalists against the results of recent theoretical work on the design of venture capital contracts, especially with regard to the use of convertible securities. First, we identify a special feature of the German market, namely that public-private partnership agencies require significantly lower returns than private and young venture capitalists. The latter are most likely to follow their North-American counterpart by refinancing themselves with closed-end funds. Second, with regard to financing practices it is shown that the use of convertibles, relative to other instruments, is influenced by the anticipated severity of agency problems. Klassifikation: C24; G24; G32
Natural resources in sub-Saharan Africa suffer from a bad reputation. Oil and diamonds, particularly, have been blamed for a number of Africa’s illnesses such as poverty, corruption, dictatorship and war. This paper outlines the different areas and transmission channels of how this so-called “resource curse” is said to materialize. By assessing empirical evidence on sub-Saharan Africa it concludes that the resource curse theory fails to sufficiently explain why and how several countries have not or only partly been affected by the “curse”. Theoretically, the paper argues that whether or not natural resources are detrimental to a country’s socio-economic and political development depends on a number of contextual variables, divided into country-specific conditions and resource-specific conditions (type, degree/level of abundance and dependence, resource revenue management, involved companies etc.). Methodologically, a future research agenda needs to examine the complex interplay of these contextual variables by adding sophisticated comparative research designs, especially “small and medium N” comparisons, to the tool box which has been widely confined to the juxtaposition of “large N” and country case studies.
Over the past decade, a variety of studies have shown that other sectors in addition to high technology industries can provide a basis for regional growth and income and employment opportunities. In addition, design-intensive, craft-based, creative industries which operate in frequently changing, fashion-oriented markets have established regional concentrations. Such industries focus on the production of products and services with a particular cultural and social content and frequently integrate new information technologies into their operations and outputs. Among these industries, the media and, more recently, multimedia industries have received particular atte ntion (Brail/ Gertler 1999; Egan/ Saxenian 1999). Especially, the film (motion picture) and TV industries have been the focus of a number of studies (e.g. Storper/ Christopherson 1987; Scott 1996). For the purpose of this paper, cultural products industries are defined as those industries which are involved in the commodification of culture, especially those operations that depend for their success on the commercialization of objects and services that transmit social and cultural messages (Scott 1996, p. 306). Empirical studies on the size, structure and organizational attributes of the firms in media-related industry clusters have revealed a number of common characteristics (Scott 1996; Brail/ Gertler 1999; Egan/ Saxenian 1999). Most firms in these industries are fairly young, often existing for only a few years. They also tend to be small in terms of employment. Often, regional clusters of specialized industries are the product of a local growth process which has been driven by innovative local start-ups. In their early stages, many firms have been established by teams of persons rather than by individual entrepreneurs and have heavily relied on owner capital. Another important feature which distinguishes these industries from others is that they concentrate in inner-city instead of suburban locations (Storper/ Christopherson 1987; Eberts/ Norcliffe 1998; Brail/ Gertler 1999). In this study, I provide evidence that the Leipzig media industry shows similar tendencies and characteristics as those displayed by the multimedia and cultural products industry clusters in Los Angeles, San Francisco and Toronto, albeit at a much smaller scale. Cultural products industries are characterized by a strong tendency towards the formation of regional clusters despite the fact that in some sectors, such as the multimedia industry, technological opportunities (i.e. internet technologies) have seemingly reduced the necessity of proximity in operations between interlinked firms. In fact, it seems that regional concentration tendencies are even more dominant in cultural products industries than in many industries of the old economy . Cultural products industries have formed particular regional clusters of suppliers, producers and customers which are interlinked within the same commodity chains (Scott 1996; Les- 2 lie/ Reimer 1999). These clusters are characterized by a deep social division of labor between vertically-linked firms and patterns of interaction and cooperation in production and innovation. Within close networks of social relations and reflexive collective action, they have developed a strong tendency towards product- and process-related specialization (Storper 1997; Maskell/ Malmberg 1999; Porter 2000). In the context of the rise of a new media industry cluster in Leipzig, Germany, I discuss those approaches in the next section of this paper which provide an understanding of complex industrial clustering processes. Therein socio-institutional settings, inter-firm communication and interactive learning play a decisive role in generating regional innovation and growth. However, I will also emphasize that interfirm networks can have a negative impact on competitiveness if social relations and linkages are too close, too exclusive and too rigid. Leipzig's historical role as a location of media-related businesses will be presented in section 3. As part of this, I will argue the need to view the present cluster of media firms as an independent phenomenon which is not a mere continuation of tradition. In section 4 the start-up and location processes are analyzed which have contributed to the rise of a new media industry cluster in Leipzig during the 1990's. Related to this, section 5 will discuss the role and variety of institutions which have developed in Leipzig and how they support specialization processes. This will be interpreted as a process of reembedding into a local context. In section 6, I will discuss how media firms have become over-embedded due to their strong orientation towards regional markets. This will be followed by some brief conclusions regarding the growth potential of the Leipzig media industry.
During the 1980s and early 1990s, the importance of small firm growth and industrial districts in Italy became the focus of a large number of regional development studies. According to this literature, successful industrial districts are characterized by intensive cooperation and market producer-user interaction between small and medium-sized, flexibly specialized firms (Piore and Sabel, 1984; Scott, 1988). In addition, specialized local labor markets develop which are complemented by a variety of supportive institutions and a tradition of collaboration based on trust relations (Amin and Robins, 1990; Amin and Thrift, 1995). It has also been emphasized that industrial districts are deeply embedded into the socio-institutional structures within their particular regions (Grabher, 1993). Many case studies have attempted to find evidence that the regional patterns identified in Italy are a reflection of a general trend in industrial development rather than just being historical exceptions. Silicon Valley, which is focused on high technology production, has been identified as being one such production complex similar to those in Italy (see, for instance, Hayter, 1997). However, some remarkable differences do exist in the institutional context of this region, as well as its particular social division of labor (Markusen, 1996). Even though critics, such as Amin and Robins (1990), emphasized quite early that the Italian experience could not easily be applied to other socio-cultural settings, many studies have classified other high technology regions in the U.S. as being industrial districts, such as Boston s Route 128 area. Too much attention has been paid to the performance of small and medium-sized firms and the regional level of industrial production in the ill-fated debate regarding industrial districts (Martinelli and Schoenberger, 1991). Harrison (1997) has provided substantial evidence that large firms continue to dominate the global economy. This does not, however, imply that a de-territorialization of economic growth is necessarily taking place as globalization tendencies continue (Storper, 1997; Maskell and Malmberg, 1998). In the case of Boston, it has been misleading to define its regional economy as being an industrial district. Neither have small and medium-sized firms been decisive in the development of the Route 128 area nor has the region developed a tradition of close communication between vertically-disintegrated firms (Dorfman, 1983; Bathelt, 1991a). Saxenian (1994) found that Boston s economy contrasted sharply with that of an industrial district. Specifically, the region has been dominated by large, vertically-integrated high technology firms which are reliant on proprietary technologies and autarkic firm structures. Several studies have tried to compare the development of the Route 128 region to Silicon Valley. These studies have shown that both regions developed into major 2 agglomerations of high technology industries in the post-World War II period. Due to their different traditions, structures and practices, Silicon Valley and Route 128 have followed divergent development paths which have resulted in a different regional specialization (Dorfman, 1983; Saxenian, 1985; Kenney and von Burg, 1999). In the mid 1970s, both regions were almost equally important in terms of the size of their high technology sectors. Since then, however, Silicon Valley has become more important and has now the largest agglomeration of leading-edge technologies in the U.S. (Saxenian, 1994). Saxenian (1994) argues that the superior performance of high technology industries in Silicon Valley over those in Boston is based on different organizational patterns and manufacturing cultures which are embedded in those socio-institutional traditions which are particular to each region. Despite the fact that Saxenian (1994) has been criticized for basing her conclusions on weak empirical research (i.e. Harrison, 1997; Markusen, 1998), she offers a convincing explanation as to why the development paths of both regions have differed.1 Saxenian s (1994) study does not, however, identify which structures and processes have enabled both regions to overcome economic crises. In the case of the Boston economy, high technology industries have proven that they are capable of readjusting and rejuvenating their product and process structures in such a way that further innovation and growth is stimulated. This is also exemplified by the region s recent economic development. In the late 1980s, Boston experienced an economic decline when the minicomputer industry lost its competitive basis and defense expenditures were drastically reduced. The number of high technology manufacturing jobs decreased by more than 45,000 between 1987 and 1995. By the mid 1990s, however, the regional economy began to recover. The rapidly growing software sector compensated for some of the losses experienced in manufacturing. In this paper, I aim to identify the forces behind this economic recovery. I will investigate whether high technology firms have uncovered new ways to overcome the crisis and the extent to which they have given up their focus on self-reliance and autarkic structures. The empirical findings will also be discussed in the context of the recent debate about the importance of regional competence and collective learning (Storper, 1997; Maskell and Malmberg, 1998). There is a growing body of literature which suggests that some regional economies During the 1980s and early 1990s, the importance of small firm growth and industrial districts in Italy became the focus of a large number of regional development studies. According to this literature, successful industrial districts are characterized by intensive cooperation and market producer-user interaction between small and medium-sized, flexibly specialized firms (Piore and Sabel, 1984; Scott, 1988). In addition, specialized local labor markets develop which are complemented by a variety of supportive institutions and a tradition of collaboration based on trust relations (Amin and Robins, 1990; Amin and Thrift, 1995). It has also been emphasized that industrial districts are deeply embedded into the socio-institutional structures within their particular regions (Grabher, 1993). Many case studies have attempted to find evidence that the regional patterns identified in Italy are a reflection of a general trend in industrial development rather than just being historical exceptions. Silicon Valley, which is focused on high technology production, has been identified as being one such production complex similar to those in Italy (see, for instance, Hayter, 1997). However, some remarkable differences do exist in the institutional context of this region, as well as its particular social division of labor (Markusen, 1996). Even though critics, such as Amin and Robins (1990), emphasized quite early that the Italian experience could not easily be applied to other socio-cultural settings, many studies have classified other high technology regions in the U.S. as being industrial districts, such as Boston s Route 128 area. Too much attention has been paid to the performance of small and medium-sized firms and the regional level of industrial production in the ill-fated debate regarding industrial districts (Martinelli and Schoenberger, 1991). Harrison (1997) has provided substantial evidence that large firms continue to dominate the global economy. This does not, however, imply that a de-territorialization of economic growth is necessarily taking place as globalization tendencies continue (Storper, 1997; Maskell and Malmberg, 1998). In the case of Boston, it has been misleading to define its regional economy as being an industrial district. Neither have small and medium-sized firms been decisive in the development of the Route 128 area nor has the region developed a tradition of close communication between vertically-disintegrated firms (Dorfman, 1983; Bathelt, 1991a). Saxenian (1994) found that Boston s economy contrasted sharply with that of an industrial district. Specifically, the region has been dominated by large, vertically-integrated high technology firms which are reliant on proprietary technologies and autarkic firm structures. Several studies have tried to compare the development of the Route 128 region to Silicon Valley. These studies have shown that both regions developed into major 2 agglomerations of high technology industries in the post-World War II period. Due to their different traditions, structures and practices, Silicon Valley and Route 128 have followed divergent development paths which have resulted in a different regional specialization (Dorfman, 1983; Saxenian, 1985; Kenney and von Burg, 1999). In the mid 1970s, both regions were almost equally important in terms of the size of their high technology sectors. Since then, however, Silicon Valley has become more important and has now the largest agglomeration of leading-edge technologies in the U.S. (Saxenian, 1994). Saxenian (1994) argues that the superior performance of high technology industries in Silicon Valley over those in Boston is based on different organizational patterns and manufacturing cultures which are embedded in those socio-institutional traditions which are particular to each region. Despite the fact that Saxenian (1994) has been criticized for basing her conclusions on weak empirical research (i.e. Harrison, 1997; Markusen, 1998), she offers a convincing explanation as to why the development paths of both regions have differed.1 Saxenian s (1994) study does not, however, identify which structures and processes have enabled both regions to overcome economic crises. In the case of the Boston economy, high technology industries have proven that they are capable of readjusting and rejuvenating their product and process structures in such a way that further innovation and growth is stimulated. This is also exemplified by the region s recent economic development. In the late 1980s, Boston experienced an economic decline when the minicomputer industry lost its competitive basis and defense expenditures were drastically reduced. The number of high technology manufacturing jobs decreased by more than 45,000 between 1987 and 1995. By the mid 1990s, however, the regional economy began to recover. The rapidly growing software sector compensated for some of the losses experienced in manufacturing. In this paper, I aim to identify the forces behind this economic recovery. I will investigate whether high technology firms have uncovered new ways to overcome the crisis and the extent to which they have given up their focus on self-reliance and autarkic structures. The empirical findings will also be discussed in the context of the recent debate about the importance of regional competence and collective learning (Storper, 1997; Maskell and Malmberg, 1998). There is a growing body of literature which suggests that some regional economies an develop into learning economies which are based on intra-regional production linkages, interactive technological learning processes, flexibility and proximity (Storper, 1992; Lundvall and Johnson, 1994; Gregersen and Johnson, 1997). In the next section of this paper, I will discuss some of the theoretical issues regarding localized learning processes, learning economies and learning regions (see, also, Bathelt, 1999). I will then describe the methodology used. What follows is a brief overview of how Boston s economy has specialized in high technology production. The main part of the paper will then focus on recent trends in Boston s high technology industries. It will be shown that the high technology economy consists of different subsectors which are not tied to a single technological development path. The various subsectors are, at least partially, dependent on different forces and unrelated processes. There is, however, tentative evidence which suggests that cooperative behavior and collective learning in supplierproducer- user relations have become important factors in securing reproductivity in the regional structure. The importance of these trends will be discussed in the conclusions.
Die Ergebnisse jüngerer Untersuchungen legen die Hypothese nahe, dass vernetzte Strukturen und eingebettetes Handeln von Unternehmen positive Auswirkungen auf deren Wettbewerbsfähigkeit hat. Die Unternehmensbefragungen der Zulieferer und Dienstleister des IPH liefern Hinweise dafür, dass dies auch für die in der chemischen Produktion tätigen Unternehmen und Betriebe gilt. Im einzelnen lassen sich aus der durchgeführten Studie folgende Ergebnisse und Tendenzen erkennen: 1. Der Zuliefer- und Dienstleistungssektor des IPH besteht aus einer großen Bandbreite von verarbeitenden Betrieben sowie Handels- und Dienstleistungsbetrieben, von denen eine Vielzahl (972 von 2435 Betrieben) in der Region ansässig sind. 2. Bei 90% der Zulieferer und Dienstleister handelt es sich um Kleinst- und Kleinbetriebe (unter 10 bzw. unter 100 Beschäftigte), die zumeist einen relativ geringen Anteil ihres Umsatzes im IPH erzielen). Lediglich 15% der befragten Betriebe sind zu mehr als der Hälfte ihrer Umsätze von den Abnehmern im IPH abhängig. 3. Die erfassten Betriebe sind vor allem über ihre Absatzbeziehungen eng in die regionale Wirtschaft eingebunden. Mehr als 50% erzielen über drei Viertel ihres Umsatzes in der Rhein-Main-Region. 4. Etwa die Hälfte der Zulieferer und Dienstleister haben durch individuelle Leistungserstellung und kundenspezifische Beratung enge Abnehmerbeziehungen zum IPH aufgebaut. Allerdings spielen besonders kommunikationsintensive Arten der Zusammenarbeit (z.B. gemeinsame Entwicklungsarbeiten und Schulungen vor Ort) offenbar nur eine geringe Rolle. 5. Die Zuliefer- und Dienstleistungsbeziehungen sind oftmals durch eine große Kontinuität und Häufigkeit gekennzeichnet. Zwar haben viele Betriebe nur jährliche oder sporadische Kontakte, die Hälfte der Betriebe stehen aber wöchentlich oder sogar täglich in Kontakt mit ihrem bedeutendsten Abnehmer im IPH. 6. Hinsichtlich der Abstimmungsinhalte zwischen den IPH-Abnehmern und ihren Zulieferern und Dienstleistern zeigt sich, dass einfache, standardisierte Kontakte (z.B. Absprache von Liefertermin und -menge) überwiegen, während komplexe Inhalte (wie gegenseitiges Feedback und gemeinsame Fehlerbeseitigung) eher selten auftreten. 7. Tendenziell haben Betriebe mit besonders regelmäßiger, individuell abgestimmter und komplexer Zusammenarbeit ihre Rolle als Zulieferer und Dienstleister des IPH in den 1990er Jahren stärken können. Bei ihnen hat sich der Anteil des IPH am Umsatz zumeist erhöht. Demgegenüber scheinen Betriebe mit seltenen, einfachen und eher standardisierten Abstimmungen im Hinblick auf ihre Umsatzentwicklung im IPH weniger erfolgreich gewesen zu sein. 37 8. Intensive Über-Kreuz-Abstimmungen zwischen den Zulieferern und Dienstleistern des IPH sind eher eine Ausnahmeerscheinung. Die meisten Betriebe haben keine Kontakte zu anderen Zulieferern und Dienstleistern. In einer anschließenden Studie soll im Rahmen einer Diplomarbeit (Bearbeiterin: Katrin Griebel) untersucht werden, ob diese Befragungsergebnisse tatsächlich die Schlussfolgerung zulassen, dass Betriebe die Möglichkeiten zu einer intensiven, komplexen Zusammenarbeit mit ihren Abnehmern im IPH nicht voll ausschöpfen und dass deshalb Potenziale für Lernprozesse und Innovationen ungenutzt bleiben. Hierzu werden im März und April 2001 Interviews mit ausgewählten Zulieferern und Dienstleistern geführt.
Using a novel experimental design, I test how the exposure to information about a group’s relative performance causally affects the members’ level of identification and thereby their propensity to harm affiliates of comparison groups. I find that both, being informed about a high and poor relative performance of the ingroup similarly fosters identification. Stronger ingroup identification creates increased hostility against the group of comparison. In cases where participants learn about poor relative performance, there appears to be a direct level effect additionally elevating hostile discrimination. My findings shed light on a specific channel through which social media may contribute to intergroup fragmentation and polarization.
How does group identity affect belief formation? To address this question, we conduct a series of online experiments with a representative sample of individuals in the US. Using the setting of the 2020 US presidential election, we find evidence of intergroup preference across three distinct components of the belief formation cycle: a biased prior belief, avoid-ance of outgroup information sources, and a belief-updating process that places greater (less) weight on prior (new) information. We further find that an intervention reducing the salience of information sources decreases outgroup information avoidance by 50%. In a social learn-ing context in wave 2, we find participants place 33% more weight on ingroup than outgroup guesses. Through two waves of interventions, we identify source utility as the mechanism driving group effects in belief formation. Our analyses indicate that our observed effects are driven by groupy participants who exhibit stable and consistent intergroup preferences in both allocation decisions and belief formation across all three waves. These results suggest that policymakers could reduce the salience of group and partisan identity associated with a policy to decrease outgroup information avoidance and increase policy uptake.
Der Einsatz von Künstliche Intelligenz (KI) – Technologien eröffnet viele Chancen, birgt aber auch viele Risiken – insbesondere in der Finanzbranche. Dieses Whitepaper gibt einen Überblick über den aktuellen Stand der Anwendung und Regulierung von KI-Technologien in der Finanzbranche, und diskutiert Chancen und Risiken von KI. KI findet in der Finanzbranche zahlreiche Anwendungsgebiete. Dazu gehören Chatbots, intelligente Assistenten für Kunden, automatischer Hochfrequenzhandel, automatisierte Betrugserkennung, Überwachung der Compliance, Gesichtserkennungssoftware zur Kundenidentifikation u. v. m. Auch Finanzaufsichtsbehörden setzen zunehmend KI-Anwendungen ein, um große und komplexe Datenmengen (Big Data) automatisiert und skalierbar auf Muster zu untersuchen und ihren Aufsichtspflichten nachzukommen.
Die Regulierung von KI in der Finanzbranche ist ein Balanceakt. Auf der einen Seite gibt es eine Notwendigkeit Flexibilität zu gewährleisten, um Innovationen nicht einzudämmen und im internationalen Wettbewerb nicht abgehängt zu werden. Strenge Auflagen können in diesem Zusammenhang als Barriere für die erfolgreiche Weiter-)Entwicklung von KI-Applikationen in der Finanzbranche wirken. Auf der anderen Seite müssen Persönlichkeitsrechte geschützt und Entscheidungsprozesse nachvollziehbar bleiben. Die fehlende Erklärbarkeit und Interpretierbarkeit von KI-Modellen entsteht in erster Linie durch Intransparenz bei einem Großteil heutiger KI-Anwendungen, bei welchen zwar die Natur der Ein- und Ausgaben beobachtbar und verständlich ist, nicht jedoch die genauen Verarbeitungsschritte dazwischen (Blackbox Prinzip).
Dieses Spannungsfeld zeigt sich auch im aktuellen regulatorischen Ansatz verschiedener Behörden. So werden einerseits die positiven Seiten von KI betont, wie Effizienz- und Effektivitätsgewinne sowie Rentabilitäts- und Qualitätssteigerungen (Bundesregierung, 2019) oder neue Methoden der Gefahrenanalyse in der Finanzmarktregulierung (BaFin, 2018a). Andererseits, wird darauf verwiesen, dass durch KI getroffene Entscheidungen immer von Menschen verantwortet werden müssen (EU Art. 22 DSGVO) und demokratische Rahmenbedingungen des Rechtsstaats zu wahren seien (FinTechRat, 2017).
Für die Zukunft sehen wir die Notwendigkeit internationale Regularien prinzipienbasiert, vereinheitlicht und technologieneutral weiterzuentwickeln, ohne dabei die Entwicklung neuer KIbasierter Geschäftsmodelle zu bremsen. Im globalen Wettstreit sollte Europa bei der Regulierung des KI-Einsatzes eine Vorreiterrolle einnehmen und damit seine demokratischen Werte der digitalen Freiheit, Selbstbestimmung und das Recht auf Information weltweit exportieren. Förderprogramme sollten einen stärkeren Fokus auf die Entwicklung nachhaltiger und verantwortungsvoller KI in Banken legen. Dazu zählt insbesondere die (Weiter-)Entwicklung breit einsetzbarer Methoden, die es erlauben, menschen-interpretierbare Erklärungen für erzeugte Ausgaben bereitzustellen und Problemen wie dem Blackbox Prinzip entgegenzuwirken.
Aus Sicht der Unternehmen in der Finanzbranche könnte eine Kooperation mit BigTech-Unternehmen sinnvoll sein, um gemeinsam das Potential der Technologie bestmöglich ausschöpfen zu können. Nützlich wäre auch ein gemeinsames semantisches Metadatenmodell zur Beschreibung der in der Finanzbranche anfallenden Daten. In Zukunft könnten künstliche Intelligenzen Daten aus sozialen Netzwerken berücksichtigen oder Smart Contracts aushandeln. Eine der größten Herausforderungen der Zukunft wird das Anwerben geeigneten Personals darstellen.
Incentives, self-selection, and coordination of motivated agents for the production of social goods
(2021)
We study, theoretically and empirically, the effects of incentives on the self-selection and coordination of motivated agents to produce a social good. Agents join teams where they allocate effort to either generate individual monetary rewards (selfish effort) or contribute to the production of a social good with positive effort complementarities (social effort). Agents differ in their motivation to exert social effort. Our model predicts that lowering incentives for selfish effort in one team increases social good production by selectively attracting and coordinating motivated agents. We test this prediction in a lab experiment allowing us to cleanly separate the selection effect from other effects of low incentives. Results show that social good production more than doubles in the low- incentive team, but only if self-selection is possible. Our analysis highlights the important role of incentives in the matching of motivated agents engaged in social good production.
In current discussions on large language models (LLMs) such as GPT, understanding their ability to emulate facets of human intelligence stands central. Using behavioral economic paradigms and structural models, we investigate GPT’s cooperativeness in human interactions and assess its rational goal-oriented behavior. We discover that GPT cooperates more than humans and has overly optimistic expectations about human cooperation. Intriguingly, additional analyses reveal that GPT’s behavior isn’t random; it displays a level of goal-oriented rationality surpassing human counterparts. Our findings suggest that GPT hyper-rationally aims to maximize social welfare, coupled with a strive of self-preservation. Methodologically, our esearch highlights how structural models, typically employed to decipher human behavior, can illuminate the rationality and goal-orientation of LLMs. This opens a compelling path for future research into the intricate rationality of sophisticated, yet enigmatic artificial agents.
Advances in Machine Learning (ML) led organizations to increasingly implement predictive decision aids intended to improve employees’ decision-making performance. While such systems improve organizational efficiency in many contexts, they might be a double-edged sword when there is the danger of a system discontinuance. Following cognitive theories, the provision of ML-based predictions can adversely affect the development of decision-making skills that come to light when people lose access to the system. The purpose of this study is to put this assertion to the test. Using a novel experiment specifically tailored to deal with organizational obstacles and endogeneity concerns, we show that the initial provision of ML decision aids can latently prevent the development of decision-making skills which later becomes apparent when the system gets discontinued. We also find that the degree to which individuals 'blindly' trust observed predictions determines the ultimate performance drop in the post-discontinuance phase. Our results suggest that making it clear to people that ML decision aids are imperfect can have its benefits especially if there is a reasonable danger of (temporary) system discontinuances.
Using experimental data from a comprehensive field study, we explore the causal effects of algorithmic discrimination on economic efficiency and social welfare. We harness economic, game-theoretic, and state-of-the-art machine learning concepts allowing us to overcome the central challenge of missing counterfactuals, which generally impedes assessing economic downstream consequences of algorithmic discrimination. This way, we are able to precisely quantify downstream efficiency and welfare ramifications, which provides us a unique opportunity to assess whether the introduction of an AI system is actually desirable. Our results highlight that AI systems’ capabilities in enhancing welfare critically depends on the degree of inherent algorithmic biases. While an unbiased system in our setting outperforms humans and creates substantial welfare gains, the positive impact steadily decreases and ultimately reverses the more biased an AI system becomes. We show that this relation is particularly concerning in selective-labels environments, i.e., settings where outcomes are only observed if decision-makers take a particular action so that the data is selectively labeled, because commonly used technical performance metrics like the precision measure are prone to be deceptive. Finally, our results depict that continued learning, by creating feedback loops, can remedy algorithmic discrimination and associated negative effects over time.
Recent regulatory measures such as the European Union’s AI Act re-quire artificial intelligence (AI) systems to be explainable. As such, under-standing how explainability impacts human-AI interaction and pinpoint-ing the specific circumstances and groups affected, is imperative. In this study, we devise a formal framework and conduct an empirical investiga-tion involving real estate agents to explore the complex interplay between explainability of and delegation to AI systems. On an aggregate level, our findings indicate that real estate agents display a higher propensity to delegate apartment evaluations to an AI system when its workings are explainable, thereby surrendering control to the machine. However, at an individual level, we detect considerable heterogeneity. Agents possess-ing extensive domain knowledge are generally more inclined to delegate decisions to AI and minimize their effort when provided with explana-tions. Conversely, agents with limited domain knowledge only exhibit this behavior when explanations correspond with their preconceived no-tions regarding the relationship between apartment features and listing prices. Our results illustrate that the introduction of explainability in AI systems may transfer the decision-making control from humans to AI under the veil of transparency, which has notable implications for policy makers and practitioners that we discuss.
This paper explores the interplay of feature-based explainable AI (XAI) tech- niques, information processing, and human beliefs. Using a novel experimental protocol, we study the impact of providing users with explanations about how an AI system weighs inputted information to produce individual predictions (LIME) on users’ weighting of information and beliefs about the task-relevance of information. On the one hand, we find that feature-based explanations cause users to alter their mental weighting of available information according to observed explanations. On the other hand, explanations lead to asymmetric belief adjustments that we inter- pret as a manifestation of the confirmation bias. Trust in the prediction accuracy plays an important moderating role for XAI-enabled belief adjustments. Our results show that feature-based XAI does not only superficially influence decisions but re- ally change internal cognitive processes, bearing the potential to manipulate human beliefs and reinforce stereotypes. Hence, the current regulatory efforts that aim at enhancing algorithmic transparency may benefit from going hand in hand with measures ensuring the exclusion of sensitive personal information in XAI systems. Overall, our findings put assertions that XAI is the silver bullet solving all of AI systems’ (black box) problems into perspective.
Conditional yield skewness is an important summary statistic of the state of the economy. It exhibits pronounced variation over the business cycle and with the stance of monetary policy, and a tight relationship with the slope of the yield curve. Most importantly, variation in yield skewness has substantial forecasting power for future bond excess returns, high-frequency interest rate changes around FOMC announcements, and consensus survey forecast errors for the ten-year Treasury yield. The COVID pandemic did not disrupt these relations: historically high skewness correctly anticipated the run-up in long-term Treasury yields starting in late 2020. The connection between skewness, survey forecast errors, excess returns, and departures of yields from normality is consistent with a theoretical framework where one of the agents has biased beliefs.
The authors estimate perceptions about the Fed's monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions is time-varying and cyclical: high during tightening episodes but low during easings. Forecasters update their perceptions about the policy rule in response to monetary policy actions, measured by high-frequency interest rate surprises, suggesting that forecasters have imperfect information about the rule. The perceived rule impacts asset prices crucial for monetary policy transmission, driving how interest rates respond to macroeconomic news and explaining term premia in long-term interest rates.
High-frequency changes in interest rates around FOMC announcements are an important tool for identifying the effects of monetary policy on asset prices and the macroeconomy. However, some recent studies have questioned both the exogeneity and the relevance of these monetary policy surprises as instruments, especially for estimating the macroeconomic effects of monetary policy shocks. For example, monetary policy surprises are correlated with macroeconomic and financial data that is publicly available prior to the FOMC announcement. The authors address these concerns in two ways: First, they expand the set of monetary policy announcements to include speeches by the Fed Chair, which essentially doubles the number and importance of announcements in our dataset. Second, they explain the predictability of the monetary policy surprises in terms of the “Fed response to news” channel of Bauer and Swanson (2021) and account for it by orthogonalizing the surprises with respect to macroeconomic and financial data. Their subsequent reassessment of the effects of monetary policy yields two key results: First, estimates of the high-frequency effects on financial markets are largely unchanged. Second, estimates of the macroeconomic effects of monetary policy are substantially larger and more significant than what most previous empirical studies have found.
High-frequency changes in interest rates around FOMC announcements are a standard method of measuring monetary policy shocks. However, some recent studies have documented puzzling effects of these shocks on private-sector forecasts of GDP, unemployment, or inflation that are opposite in sign to what standard macroeconomic models would predict. This evidence has been viewed as supportive of a „Fed information effect“ channel of monetary policy, whereby an FOMC tightening (easing) communicates that the economy is stronger (weaker) than the public had expected.
The authors show that these empirical results are also consistent with a „Fed response to news“ channel, in which incoming, publicly available economic news causes both the Fed to change monetary policy and the private sector to revise its forecasts. They provide substantial new evidence that distinguishes between these two channels and strongly favors the latter; for example, regressions that include the previously omitted public macroeconomic news, high-frequency stock market responses to Fed announcements, and a new survey that they conduct of individual Blue Chip forecasters all indicate that the Fed and private sector are simply responding to the same public news, and that there is little if any role for a „Fed information effect“.
Gegenstand dieser Arbeit sind die englischen Lehnwörter des Samoanischen, einer westpolynesischen Sprache. Als Basis der Untersuchung und Quelle des bearbeiteten Lehnwortschatzes dient das "Lexicon of foreign loan-words in the Samoan language" von Cain (1986)1. Hierbei handelt es sich um eine Auflistung der lexikalischen Entlehnungen im Samoanischen mit kurzen enzyklopädischen Erläuterungen. Ziel der vorliegenden Arbeit soll sein, die Integration der englischen Lehnwörter in die samoanische Sprache darzustellen und gegebenenfalls Regularitäten bezüglich der Assimilation an das samoanische Phoneminventar aufzuzeigen.
It is commonly believed that the response of the price of corn ethanol (and hence of the price of corn) to shifts in biofuel policies operates in part through market expectations and shifts in storage demand, yet to date it has proved difficult to measure these expectations and to empirically evaluate this view. We utilize a recently proposed methodology to estimate the market’s expectations of the prices of ethanol, unfinished motor gasoline and crude oil at horizons from three months to one year. We quantify the extent to which price changes were anticipated by the market, the extent to which they were unanticipated, and how the risk premium in these markets has evolved. We show that the Renewable Fuel Standard (RFS) is likely to have increased ethanol price expectations by as much $1.45 in the year before and in the year after the implementation of the RFS had started. Our analysis of the term structure of expectations provides support for the view that a shift in ethanol storage demand starting in 2005 caused an increase in the price of ethanol. There is no conclusive evidence that the tightening of the RFS in 2008 shifted market expectations, but our analysis suggests that policy uncertainty about how to deal with the blend wall raised the risk premium in the ethanol futures market in mid-2013 by as much as 50 cents at longer horizons. Finally, we present evidence against a tight link from ethanol price expectations to corn price expectations and hence to storage demand for corn in 2005-06.
The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. An obvious advantage of financial data in forecasting oil prices is their availability in real time on a daily or weekly basis. We investigate whether mixed-frequency models may be used to take advantage of these rich data sets. We show that, among a range of alternative high-frequency predictors, especially changes in U.S. crude oil inventories produce substantial and statistically significant real-time improvements in forecast accuracy. The preferred MIDAS model reduces the MSPE by as much as 16 percent compared with the no-change forecast and has statistically significant directional accuracy as high as 82 percent. This MIDAS forecast also is more accurate than a mixed-frequency realtime VAR forecast, but not systematically more accurate than the corresponding forecast based on monthly inventories. We conclude that typically not much is lost by ignoring high-frequency financial data in forecasting the monthly real price of oil.
Futures markets are a potentially valuable source of information about market expectations. Exploiting this information has proved difficult in practice, because the presence of a time-varying risk premium often renders the futures price a poor measure of the market expectation of the price of the underlying asset. Even though the expectation in principle may be recovered by adjusting the futures price by the estimated risk premium, a common problem in applied work is that there are as many measures of market expectations as there are estimates of the risk premium. We propose a general solution to this problem that allows us to uniquely pin down the best possible estimate of the market expectation for any set of risk premium estimates. We illustrate this approach by solving the long-standing problem of how to recover the market expectation of the price of crude oil. We provide a new measure of oil price expectations that is considerably more accurate than the alternatives and more economically plausible. We discuss implications of our analysis for the estimation of economic models of energy-intensive durables, for the debate on speculation in oil markets, and for oil price forecasting.