Inference with Dependent Data in Accounting and Finance Applications

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.     

International Transmission Channels of U.S. Quantitative Easing: Evidence from Canada

The U.S. Federal Reserve responded to the great recession by implementing quantitative easing, or large‐scale asset purchases, when its conventional policy rate reached the zero lower bound. We assess the international spillover effects of this quantitative easing program on the Canadian economy in a factor‐augmented vector autoregression (FAVAR) framework, by considering a counterfactual scenario in which the Federal Reserve's long‐term asset holdings do not rise in response to the recession. We find that U.S. quantitative easing boosted Canadian output, mainly through the financial channel.     

Monetary Policy,Trend Inflation,and Unemployment Volatility

The literature has long agreed that the DMP model (after Diamond 1982, Mortensen 1982, Pissarides 1985) with search and matching frictions in the labor market can deliver large volatilities in labor market quantities, consistent with empirical data, only if there is at least some wage stickiness. I show, however, that the model can deliver nontrivial volatilities without wage stickiness, as long as it has price dispersion and nonzero long‐run inflation rates. I find that by keeping inflation at a positive rate, monetary policy may be accountable for the large standard deviations observed on labor market variables. In addition, the Shimer (2005) puzzle disappears under monetary policy shocks.     

Raise Rates to Raise Inflation? Neo‐Fisherianism in the New Keynesian Model

Increasing the inflation target in a New Keynesian (NK) model may require increasing, rather than decreasing, the nominal interest rate in the short run. We refer to this positive short‐run comovement between the nominal rates and inflation conditional on a nominal shock as Neo‐Fisherianism. We show that the NK model is more likely to be Neo‐Fisherian the more persistent is the change in the inflation target and the more flexible are prices. Neo‐Fisherianism is driven by the forward‐looking nature of the model. Modifications that make the framework less forward‐looking make it less likely for the model to exhibit Neo‐Fisherianism.     

Financial Stress Regimes and the Macroeconomy

Some financial stress events lead to macroeconomic downturns, while others appear to be isolated to financial markets. We identify financial stress regimes using a model that explicitly links financial variables to macro‐economic outcomes. The stress regimes are identified using an unbalanced panel of financial variables with an embedded method for variable selection. Our identified stress regimes are associated with corporate credit tightening and with NBER recessions. An exogenous deterioration in our financial conditions index has strong negative effects in economic activity, and negative amplification effects on inflation in the stress regime. These results are obtained with a novel factor‐augmented vector autoregressive model with smooth‐transition regimes (FASTVAR).     

Partial moment volatility indices

Forward‐looking partial moment volatility indices are developed using state‐pricing, called the bear index (BEX) and bull index (BUX). Using S&P 500 index (SPX) option prices, we find that BEX and BUX provide superior forecasts for the lower and upper partial moments of future market realised volatility, respectively. We examine the relation between SPX returns and changes in BEX and BUX at the daily level. Results are consistent with the volatility feedback hypothesis. Further, we show that BEX may be more suitable as the ‘investor fear gauge’ than VIX.     

Board governance and corporate performance

We examine the link between the monitoring capacity of the board and corporate performance of UK listed firms. We also investigate how firms use the flexibility offered by the voluntary governance regime to make governance choices. We find a strong positive association between the board governance index we construct and firm operating performance. Our results imply that adherence to the board‐related recommendations of the UK Corporate Governance Code strengthens the board's monitoring capacity, potentially helping mitigate agency problems, but that investors do not value it correspondingly. Moreover, in contrast to prior UK findings suggesting efficient adoption of Code recommendations, we find that firms at times use the Code flexibility opportunistically, aiming to decrease the monitoring capacity of the board, which is followed by subsequent underperformance. This finding questions the effectiveness of the voluntary approach to governance regulation followed in the UK and in many countries around the world.     

Marriage between credit cards and the Internet: Buying is just a click away!

This paper examines whether Internet access positively affects credit card balances. To that end, we compare the 2010 and 2013 Surveys of Consumer Finances, analyze the consistency of the results over time, and provide the rationale for any resulting differences. Using the censored techniques, our results indicate that Internet access has a positive effect on credit card balances, which suggests that consumers with Internet access are prone to higher balances compared to those without. The probability of carrying positive balances was larger in 2010 compared to 2013. Overall, the results suggest that, while the financial crisis might have contributed to higher balances in 2010, the economic recovery afterward seems to have eased the burden of credit card debt.     

Inclusion climate: A multilevel investigation of its antecedents and consequences

This study investigates the antecedents and consequences of organization‐level inclusion climate. A national sample of human resource decision‐makers from 100 organizations described their firms' formal diversity management programs; 3,229 employees reported their perceptions of, and reactions to, their employers' diversity management. Multilevel analyses demonstrate that identity‐conscious programs (programs that target specific identity groups) generate an inclusion climate. Moreover, the analyses provide evidence of multilevel mediation: In organizations with an inclusion climate, individual employees perceive the organization as fulfilling its diversity management obligations and respond with higher levels of affective commitment. This study represents an important step toward understanding how a shared perception of organizational inclusiveness develops and how inclusion climate facilitates the achievement of diversity management objectives. The findings also shed light on the important role of identity‐conscious programs in promoting organizational commitment within a diverse workforce.     

Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.