Information Transparency in Multi-Channel B2B Auctions: A Field Experiment

With the large amount of data available via different channels, firms have increasingly viewed information transparency as an important component of their strategy. This paper examines how the disclosure of winners\u27 information affects sellers\u27 revenues in multi-channel, B2B sequential auctions. Using a field experiment, we find that bidders tend to pay higher prices when winners\u27 identities are concealed from public view. At the outset, such finding contradicts the prediction of the well-known linkage principle in auction theory. Our empirical analysis suggests that anonymizing winning bids might discourage tacit collusion and mitigate the declining price trend in these B2B sequential auctions. This paper contributes to the growing literature on information transparency in market design. It also provides valuable insights to practitioners in designing information revelation policies in complex B2B markets

Promoting Regulatory Prediction

It is essential for environmental protection that private actors be able to anticipate government regulation. If, for instance, the Biden Administration is planning to tighten regulations of greenhouse gas emissions, it is imperative that private companies anticipate this regulatory change now, not a few years from now after they have constructed even more coal- and gas-fired power plants. Those additional power plants will mean more irreversible greenhouse gases, and these plants can be politically challenging to shutter once built. The point is general to private actors making decisions in the shadow of potential government regulation. Better information about future government actions is thus critical for the benefit of both private actors and society at large. In this Article, we consider market-based and non-market-based means by which to generate information about future government action. We find no perfect answer. We consider three market-based solutions—prediction markets, the use of equity markets to hedge against future government action, and machine-learning and predictive technologies—and three government-based solutions—greater transparency, the development of intellectual property rights in predictive information, and prediction-forcing regulation, which is regulation that requires private actors to make public predictions about future government action. None of these is a panacea. The market-based solutions founder on the limitations and thinness of markets. Government-based solutions come with significant structural downsides related to the division of authority among different levels of government (federal versus state versus local) and different branches of government at each level (executive versus legislative). We conclude that prediction-forcing regulation may be the most promising avenue, though it too is likely not a full solution

Promoting Regulatory Prediction

It is essential for environmental protection that private actors be able to anticipate government regulation. If, for instance, the Biden Administration is planning to tighten regulations of greenhouse gas emissions, it is imperative that private companies anticipate this regulatory change now, not a few years from now after they have constructed even more coal- and gas-fired power plants. Those additional power plants will mean more irreversible greenhouse gases, and these plants can be politically challenging to shutter once built. The point is general to private actors making decisions in the shadow of potential government regulation. Better information about future government actions is thus critical for the benefit of both private actors and society at large. In this Article, we consider market-based and non-market-based means by which to generate information about future government action. We find no perfect answer. We consider three market-based solutions—prediction markets, the use of equity markets to hedge against future government action, and machine-learning and predictive technologies—and three government-based solutions—greater transparency, the development of intellectual property rights in predictive information, and prediction-forcing regulation, which is regulation that requires private actors to make public predictions about future government action. None of these is a panacea. The market-based solutions founder on the limitations and thinness of markets. Government-based solutions come with significant structural downsides related to the division of authority among different levels of government (federal versus state versus local) and different branches of government at each level (executive versus legislative). We conclude that prediction-forcing regulation may be the most promising avenue, though it too is likely not a full solution

Location Advantages, Governance Quality, Stock Market Development and Firm Characteristics as Antecedents of African M&As

This study explores firm- and country-specific antecedents of African M&As. We use one of the largest datasets to-date consisting of 1,490 unique African firms (11,183 firm-year observations) from 1996 to 2012. Our results suggest that improvements in time-varying country-level factors, including location advantages (market size, human capital and efficiency opportunities), national governance quality, and stock market development are associated with an increase in the volume of M&A activity. Consistent with the resource-curse paradox, high resource endowments are not associated with increased levels of M&A. In support of the management inefficiency but contrary to the traditional firm size hypotheses, African targets are generally characterised by declining stock returns and accounting profitability but are more likely to be larger firms; suggesting the presence of information asymmetry concerns in their selection. Notwithstanding, we find evidence of heterogeneity across countries with inconsistent support for established target prediction hypotheses. A model which combines firm- and country- specific factors better explains observed variations in African M&A activity

Trade disclosure and price dispersion

This paper determines the effects of post-trade opaqueness on market performance. We find that the degree of market transparency has important effects on market equilibria. In particular, we show that dealers operating in a transparent structure set regret-free prices at each period making zero expected profits in each of the two trading rounds, whereas in the opaque market dealers invest in acquiring information at the beginning of the trading day. Moreover, we obtain that if there is no trading activity in the first period, then market makers only change their quotes in the opaque market. Additionally, we show that trade disclosure increases the informational efficiency of transaction prices and reduces volatility. Finally, concerning welfare of market participants, we obtain ambiguous results

Trade disclosure and price dispersion

This paper studies the implications of trade reporting in a two-stage trade model similar to Journal of Financial Economics 14, 71–100. We find that the degree of market transparency has important effects on market equilibria. In particular, we show that dealers operating in a transparent structure set regret-free prices at each period. In contrast, dealers in an opaque market invest in acquiring information at the beginning of the trading day. Moreover, we show that in equilibrium there is price dispersion in the opaque market, whereas this is not the case if orders are reported. Additionally, we show that trade disclosure increases the informational efficiency of transaction prices and reduces volatility. Finally, concerning the welfare of market participants, we obtain ambiguous results.Publicad

Monetary policy transparency and private sector forecasts: evidence from survey data

In recent years, central banks around the world have greatly increased the monetary policy information they have provided the public. The Federal Reserve has taken a number of actions to promote transparency including, most recently, the announcement of enhancements to the FOMC's (Federal Open Market Committee) economic forecasts that are released to the public. ; The movement toward increased transparency arises largely from the view that increased transparency has important benefits, including more effective monetary policy. This view is based on theoretical and empirical research that has emphasized the importance of public expectations about monetary policy as a key factor in determining interest rates and other asset prices. In particular, this research suggests that improved predictability of monetary policy may reduce the volatility of asset prices and make monetary policy more effective by increasing a central bank's leverage over longer-term interest rates. ; Sellon uses information from the Blue Chip Long Range Financial Forecasts to examine whether longer-horizon predictability has been associated with increased transparency. The analysis suggests several interesting conclusions. First, consistent with previous studies using futures data, there has been a marked reduction in survey forecast errors at short-term horizons. But, the survey data suggest there has been much less improvement at longer horizons. Second, to the extent private sector longer-horizon forecasts of future monetary policy have improved in recent years, most of the improvement occurred from 2003 to 2006, when the Federal Reserve provided more explicit guidance about the future path of the federal funds rate. During this period, forecast errors over all horizons dropped remarkably. Indeed, this period appears to have driven most of the improvement in the Blue Chip survey forecasts seen over the entire 1986-2007 sample period. Third, the survey evidence reported in this article does not support the finding of some studies that forecasting improved suddenly after 1994. Fourth, the longer-horizon forecast errors have been largest when policy was being actively tightened or eased, especially during the 1990-92 and 2001-03 periods of extended policy easing. Finally, longer-horizon forecast errors appear to have diminished during periods of tightening, but not during periods of easing.

Grid Integration Costs of Fluctuating Renewable Energy Sources

The grid integration of intermittent Renewable Energy Sources (RES) causes costs for grid operators due to forecast uncertainty and the resulting production schedule mismatches. These so-called profile service costs are marginal cost components and can be understood as an insurance fee against RES production schedule uncertainty that the system operator incurs due to the obligation to always provide sufficient control reserve capacity for power imbalance mitigation. This paper studies the situation for the German power system and the existing German RES support schemes. The profile service costs incurred by German Transmission System Operators (TSOs) are quantified and means for cost reduction are discussed. In general, profile service costs are dependent on the RES prediction error and the specific workings of the power markets via which the prediction error is balanced. This paper shows both how the prediction error can be reduced in daily operation as well as how profile service costs can be reduced via optimization against power markets and/or active curtailment of RES generation.Comment: Accepted for SUSTECH 2014, Portland, Oregon, USA, July 201

Information sharing and credit : firm-level evidence from transition countries

We investigate whether information sharing among banks has affected credit market performance in the transition countries of Eastern Europe and the former Soviet Union, using a large sample of firm-level data. Our estimates show that information sharing is associated with improved availability and lower cost of credit to firms. This correlation is stronger for opaque firms than transparent ones and stronger in countries with weak legal environments than in those with strong legal environments. In cross-sectional estimates, we control for variation in country-level aggregate variables that may affect credit, by examining the differential impact of information sharing across firm types. In panel estimates, we also control for the presence of unobserved heterogeneity at the firm level, as well as for changes in macroeconomic variables and the legal environment