Investor behaviour and reaching for yield: Evidence from the sterling corporate bond market

We provide evidence on how corporate bond investors react to a change in yields, and how this behaviour differs in times of market‐wide stress. We also investigate ‘reaching for yield’ across investor types, as well as providing insights into the structure of the corporate bond market. Using proprietary sterling corporate bond transaction data, we show that insurance companies, hedge funds and asset managers are typically net buyers when corporate bond yields rise. Dealer banks clear the market by being net sellers. However, we find evidence for this behaviour reversing in times of stress for some investors. During the 2013 ‘taper tantrum’, asset managers were net sellers of corporate bonds in response to a sharp rise in yields, potentially amplifying price changes. At the same time, dealer banks were net buyers. Finally, we provide evidence that insurers, hedge funds and asset managers tilt their portfolios towards higher risk bonds, consistent with ‘reaching for yield’ behaviour.     

Cultural Baggage: Do Immigrants Import Corruption?

Do immigrants undermine culture in a way that destroys productivity in destination countries? Some scholars have argued that because immigrants come from countries with dysfunctional social capital—norms and institutions—they will import it and pollute the social capital in destination countries. One potential channel through which this could occur is corruption. We examine stocks and flows of immigrants over a 20‐year time period to see if corruption increased in destination countries. We generally find that immigration is not associated with increases in corruption. Additionally, we find that immigration tends to decrease corruption in destination countries with low levels of corruption or high levels of economic freedom.     

Panel LM unit root tests with level and trend shifts

This paper considers a Lagrange multiplier (LM) based panel unit root test that allows for heterogeneous structural breaks in both the intercepts and slopes of a series. We note that many popular time series variables are likely to exhibit changing means and/or trends over time. Given that the usual tests will depend on the nuisance parameters indicating the locations of the trend breaks, we adopt a transformation procedure that makes our new panel unit root tests invariant to the nuisance parameters. To illustrate the importance of the power gain provided by our test, we examine the convergence hypothesis using relative ratios of per capita health care expenditures in 20 OECD countries. Our results provide evidence that the convergence hypothesis is supported.     

EMPIRICAL PERFORMANCE OF GARCH MODELS WITH HEAVY‐TAILED INNOVATIONS

We introduce a new type of heavy‐tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten‐Jagannathan‐Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy‐tailed distribution, the Student's t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR‐terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR‐GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum‐likelihood estimation of GARCH and GJR‐GARCH models with the three types of heavy‐tailed distribution is investigated.     

Change-point detection for expected shortfall in time series

Expected shortfall (ES) is a popular risk measure and plays an important role in risk and portfolio management. Recently, change-point detection of risk measures has been attracting much attention in finance. Based on the self-normalized CUSUM statistic in Fan, Glynn and Pelger (2018) and the Wild Binary Segmentation (WBS) algorithm in Fryzlewicz (2014), this paper proposes a variant WBS procedure to detect and estimate change points of ES in time series. The strengthened Schwarz information criterion is also introduced to determine the number of change points. Monte Carlo simulation studies are conducted to assess the finite-sample performance of our variant WBS procedure about ES in time series. An empirical application is given to illustrate the usefulness of our procedure.     

Is the Optimal Labor Income Tax Progressive in a Unionized Economy?*

This paper concerns optimal nonlinear labor income taxation in an economy with union wage setting and endogenous hours of work. The purpose is to study the determinants of tax progression. We show that the optimal degree of progression of the labor income tax depends on the extent to which the government can influence the wage rate via tax policy as well as on its ability to redistribute income across individuals. In addition, the argument for progressive labor income taxation depends on whether hours of work are chosen by the employed themselves or the union.     

Cities under stress

This paper studies the effect of terrorist attacks on the internal structure of cities. We develop an urban framework with capital structures suitable for the study of this question and analyze the long and short term implications of this type of events. In the long run, the analysis shows that a terrorist attack will affect urban structure only modestly, relative to the potentially large decrease in the level of economic activity in the city. Land rents will not decline at all locations. In the short run, agglomeration forces will amplify the effect of the original destruction and will reduce urban economic activity temporarily.     

Unit roots and infrequent large shocks: new international evidence on output

The nature and magnitude of the economic shocks that have affected the per capita GDP of 16 OECD countries are analyzed over a long period using the outlier method. Strong proof of infrequent large permanent and transitory shocks were found, essentially resulting from the two major wars in the twentieth century, the recession in the 1920s, the Great Depression, among others. We also examine the nature of the output trend by combining different tests of non-stationarity on different GDP series corrected by the outliers detected. It is shown that the per capita GDP series cannot reject the unit root hypothesis in 13 of the 16 countries examined. No conclusion could be drawn for the other countries because the test results were contradictory.     

Separating microstructure noise from volatility

There are two variance components embedded in the returns constructed using high frequency asset prices: the time-varying variance of the unobservable efficient returns that would prevail in a frictionless economy and the variance of the equally unobservable microstructure noise. Using sample moments of high frequency return data recorded at different frequencies, we provide a simple and robust technique to identify both variance components.     

Technological innovation and real investment booms and busts

We investigate why new, high-risk technologies can attract excessive and often unprofitable investment. We develop an equilibrium model in which rational, risk-averse agents overinvest in a risky technology, possibly to the point that its expected return is negative. Overinvestment results from relative wealth concerns which arise endogenously from the imperfect tradability of future endowments. Competition over future consumption leads to an indirect utility for wealth with “keeping up with the Joneses” properties that can induce herding. Because overinvestment increases with the risk of the technology, our model can explain why new, risky technological innovations may promote investment bubbles.