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This paper studies the impact of financial sector size and leverage on business cycles and risk-free rates dynamics. We model a general equilibrium productive economy where financial intermediaries provide costly risk mitigation to households by pooling the idiosyncratic risks of their investment activities. We find that leverage amplifies variations of intermediaries’ relative size, but may also mitigate the business cycle. Moreover, it makes risk-free rates pro-cyclical. Households benefit the most when the financial sector is neither too small, thus avoiding high consumption fluctuations and costly mitigation, nor too big, so that fewer resources are lost after intermediation costs.
We show that High Frequency Traders (HFTs) are not beneficial to the stock market during flash crashes. They actually consume liquidity when it is most needed, even when they are rewarded by the exchange to provide immediacy. The behavior of HFTs exacerbate the transient price impact, unrelated to fundamentals, typically observed during a flash crash. Slow traders provide liquidity instead of HFTs, taking advantage of the discounted price. We thus uncover a trade-o↵ between the greater liquidity and efficiency provided by HFTs in normal times, and the disruptive consequences of their trading activity during distressed times.
Law is force of order. It reacts, usually with a necessary time delay, to technological pro-gress. Only twelve years after Samuel Morse presented the first workable telegraph sys-tem in New York in 1838 and six years after the first completed telegraph line from Wash-ington to Baltimore, central European states agreed on an international framework for tel-egraphs. It has been much more than twelve years since the technologies underlying the internet’s popularity today, such as the ‘World Wide Web’, were invented. No international framework has emerged, even though normative approaches abound. There are norms that are applied to the internet, but the recognition of the existence of an underlying, structuring order is missing. This motivates the present study.
This paper presents causal evidence of the effects of boardroom networks on firm value. We exploit exogenous variation in network centrality arising from a ban on interlocking directorates of Italian financial and insurance companies. We leverage this shock to show that firms that become more central in the network as a result of the shock experience positive abnormal returns around the announcement date. We find that information dissemination plays a central role: results are driven by firms that have higher idiosyncratic volatility, low analyst coverage, and more uncertainty surrounding their earnings forecasts. We also find that firms benefit more from boardroom centrality when they are more central in the input-output network, as this reinforces information complementarities, or when they are less central in the cross-ownership network, as well as when they suffer from low profitability and low growth opportunities. Network centrality also results in higher compensation for board directors.
Using an original dataset on professional networks of directors sitting on the boards of large US corporations, we examine how personal relationships are used by firms to improve job match quality in the high-skill segment of the labor market. Analyzing explicit social connection data between new hires and recruiters, we are able to test predictions of well established job referral models. We find that referred executive directors have a fifteen percent longer tenure than their non-referred counterparts. Referred executive directors also tend to be similar to their referrers on multiple dimensions, giving support to network homophily hypotheses.
We study whether and how time preferences change over the life cycle, exploiting representative long-term panel data. We estimate the age patterns of discount rates from age 25 to 80. In order to identify age effects, we have to disentangle them from cohort and period factors. We address this identification problem by estimating individual fixed effects models, where we substitute period effects with determinants of time preferences that depend on calendar years. We find that discount rates decrease with age and the decline is remarkably linear over the life cycle.
In many parts of the world, the centralized grid provides energy to the population only to a limited extent. The electrification for sub-Saharan Africa countries is the lowest in the world, representing half of the world's population withoutelectricity. However, during the last years there has been an increased attention to rural areas in the Global South beyond the centralised grid, especially with respect to improved possibilities of solar power systems. The transition from one dominant form of energy provision to various alternatives includes different dimensions and depends on specific socio-spatial contexts. Energy systems are framed within systems of spatial practices, performed by a variety of involved actors, like consumers, local suppliers, international for-profit companies, international development donors as well as national and regional authorities. As such power systems arealways cause and effect of socio-technical change This study takes the example of Rwanda to analyse the marketization of decentralised energy systems. Based on empirical field work with energy entrepreneurs it combines Post-Colonial Theory with Science and Technology-Studies to theorise the role of energy to the social production of space beyond the grid.
In this paper we argue that the own findings of the SSM THEMATIC REVIEW ON PROFITABILITY AND BUSINESS MODEL and the academic literature on bank profitability do not provide support for the business model approach of supervisory guidance. We discuss in the paper several reasons why the regulator should stay away from intervening in management practices. We conclude that by taking the role of a coach instead of a referee, the supervisor generates a hazard for financial stability.
Discussions about the banking union have restarted. Its success so far is limited: national banking sectors are still overwhelmingly exposed to their own countries’ economies, cross border banking has not increased and capital and liquidity remain locked within national boundaries. The policy letter highlights that the current debate, centered on sovereign exposures and deposit insurance, misses critical underlying problems in the supervision and resolution frameworks. The ECB supervisors’ efforts to facilitate cross-border banking have been hampered by national ringfencing. The resolution framework is not up to its task: limited powers of the SRB, prohibitive access conditions and limited size of the Single Resolution Fund limit its effectiveness. A lack of a coherent European framework for insolvency unlevels the regulatory field and creates incentives to bypass European rules. The new Commission and European Parliament, with the new ECB leadership, provide a unique opportunity to address these shortcomings and make the banking union work.
The term structure of interest rates is crucial for the transmission of monetary policy to financial markets and the macroeconomy. Disentangling the impact of monetary policy on the components of interest rates, expected short rates and term premia, is essential to understanding this channel. To accomplish this, we provide a quantitative structural model with endogenous, time-varying term premia that are consistent with empirical findings. News about future policy, in contrast to unexpected policy shocks, has quantitatively significant effects on term premia along the entire term structure. This provides a plausible explanation for partly contradictory estimates in the empirical literature.
We design, field and exploit survey data from a representative sample of the French population to examine whether informative social interactions enter householdsístockholding decisions. Respondents report perceptions about their circle of peers with whom they interact about Önancial matters, their social circle and the population. We provide evidence for the presence of an information channel through which social interactions ináuence perceptions and expectations about stock returns, and financial behavior. We also find evidence of mindless imitation of peers in the outer social circle, but this does not permeate as many layers of financial behavior as informative social interactions do.
Abundant studies show that individuals often struggle and frequently fail to form a correct perception of how much they are worth in terms of income or net wealth, both in absolute terms and relative to others. The authors find that wealth misperception arises even in a frictionless environment. They show that this wealth misperception is related to low cognitive abilities and inattention, and that subjects who misperceive wealth have a greater tendency to borrow and spend out of gains. A standard optimal consumption choice model, enriched with a rational but inattentive agent à la Gabaix aligns the key experimental findings.
This paper provides an overview of how to use "big data" for economic research. We investigate the performance and ease of use of different Spark applications running on a distributed file system to enable the handling and analysis of data sets which were previously not usable due to their size. More specifically, we explain how to use Spark to (i) explore big data sets which exceed retail grade computers memory size and (ii) run typical econometric tasks including microeconometric, panel data and time series regression models which are prohibitively expensive to evaluate on stand-alone machines. By bridging the gap between the abstract concept of Spark and ready-to-use examples which can easily be altered to suite the researchers need, we provide economists and social scientists more generally with the theory and practice to handle the ever growing datasets available. The ease of reproducing the examples in this paper makes this guide a useful reference for researchers with a limited background in data handling and distributed computing.
We introduce Implied Volatility Duration (IVD) as a new measure for the timing of uncertainty resolution, with a high IVD corresponding to late resolution. Portfolio sorts on a large cross-section of stocks indicate that investors demand on average about seven percent return per year as a compensation for a late resolution of uncertainty. In a general equilibrium model, we show that `late' stocks can only have higher expected returns than `early' stocks if the investor exhibits a preference for early resolution of uncertainty. Our empirical analysis thus provides a purely market-based assessment of the timing preferences of the marginal investor.
We study the incidence and severity of lower-bound episodes and the efficacy of three types of state-dependent policies—forward guidance about the future path of interest rates, large-scale asset purchases and spending-based fiscal stimulus—in ameliorating the adverse consequences stemming from the effective lower bound on nominal interest rates. In particular, we focus on the euro area economy and examine, using the ECB’s New Area- Wide Model, the consequences of the lower bound both for the near-term economic outlook, characterised by persistently low nominal interest rates and inflation, and in a lasting low-real-interest-rate world. Our findings suggest that, if unaddressed, the lower bound can have very substantial costs in terms of worsened macroeconomic performance. Forward guidance, if fully credible, is most powerful and can largely undo the distortionary effects due to the lower bound. A combination of imperfectly credible forward guidance, asset purchases and fiscal stimulus is almost equally effective, in particular when asset purchases enhance the credibility of the forward guidance policy via a signalling effect.
Differential games of common resources that are governed by linear accumulation constraints have several applications. Examples include political rent-seeking groups expropriating public infrastructure, oligopolies expropriating common resources, industries using specific common infrastructure or equipment, capital-flight problems, pollution, etc. Most of the theoretical literature employs specific parametric examples of utility functions. For symmetric differential games with linear constraints and a general time-separable utility function depending only on the player’s control variable, we provide an exact formula for interior symmetric Markovian-strategies. This exact solution, (a) serves as a guide for obtaining some new closed-form solutions and for characterizing multiple equilibria, and (b) implies that, if the utility function is an analytic function, then the Markovian strategies are analytic functions, too. This analyticity property facilitates the numerical computation of interior solutions of such games using polynomial projection methods and gives potential to computing modified game versions with corner solutions by employing a homotopy approach.
This paper focuses on the life and work of three of the most important men who arrived in the Philippines during the 16th century: the Augustinian Martín de Rada (1533–1578) studied at the universities of Paris and Salamanca. He was one of the best European scientists of his time in East Asia. The Dominican Domingo de Salazar (1512–1594), first bishop of Manila, studied the legitimacy of the conquest of the Philippines and wrote against the Spanish plan to conquest China. The Dominican Juan Cobo (? –1592) was the first Spanish to master the Chinese language and, through his book Shilu, the first European who introduced Christianity to the Chinese from a rational point of view and the first one to introduce European science into Chinese context. All of them were very influenced by the School of Salamanca and, from Manila, they always had their eyes on China. These three men of the late 16th century are paradigmatic examples of the influence of the University of Salamanca in the production of global knowledge in the early modernity.
Differences in euro-area household finances and their relevance for monetary-policy transmission
(2019)
This paper quantifies the extent of heterogeneity in consumption responses to changes in real interest rates and house prices in the four largest economies in the euro area: France, Germany, Italy, and Spain. We first calibrate a life-cycle incomplete-markets model with a financial asset and housing to match the large heterogeneity of households asset portfolios, observed in the Household Finance and Consumption Survey (HFCS) for these countries. We then show that the heterogeneity in household finances implies that responses of consumption to changes in the real interest rate and in house prices differ substantially across countries, and within countries by household characteristics such as age, housing tenure, and asset positions. The different consumption responses quantified in this paper point towards important heterogeneity in monetary-policy transmission in the euro area.
Is it true that speed bumps level the playing field, make financial markets more stable and reduce negative externalities of high-frequency trading (HFT) firms? We examine how the implementation of a particular speed bump – Midpoint Extended Life order (M-ELO) on Nasdaq impacted financial markets stability in terms of occurrences of mini-flash crashes in individual securities. We use high-frequency order book message data around the implementation date and apply difference-in-differences analysis to estimate the average treatment effect of the speed bump on market stability and liquidity provision. The results suggest that the introduction of the M-ELO decreases the average number of crashes on Nasdaq compared to other exchanges by 4.7%. Liquidity provision by HFT firms also improves. These findings imply that technology-based solutions by exchanges are feasible alternatives to regulatory intervention towards safer markets.
We study the accuracy and usefulness of automated (i.e., machine-generated) valuations for illiquid and heterogeneous real assets. We assemble a database of 1.1 million paintings auctioned between 2008 and 2015. We use a popular machine-learning technique—neural networks—to develop a pricing algorithm based on both non-visual and visual artwork characteristics. Our out-of-sample valuations predict auction prices dramatically better than valuations based on a standard hedonic pricing model. Moreover, they help explaining price levels and sale probabilities even after conditioning on auctioneers’ pre-sale estimates. Machine learning is particularly helpful for assets that are associated with high price uncertainty. It can also correct human experts’ systematic biases in expectations formation—and identify ex ante situations in which such biases are likely to arise.