Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

The Impact of Employment on Parental Coresidence

We examine the extent to which parents use housing and shared living arrangements as a form of risk‐sharing for their adult children, using detailed data on children and parents in the Health and Retirement Study for 1998–2012. On average, a young man moving from full‐time to nonemployment raises the likelihood of coresiding with a parent by 1.5 percentage points; moving from full‐time employment to being part‐time employed raises the likelihood of coresiding with a parent by 2 percentage points. The implied elasticity of parental coresidence with respect to the son's income is ‐1.1; for daughters, the elasticity is ‐0.5.     

CEO internal experience and voluntary disclosure quality: Evidence from management forecasts

Internally‐promoted CEOs should have a deep understanding of their firm's products, supply chain, operations, business climate, corporate culture, and how to navigate among employees to get the information they need. Thus, we argue that internally‐promoted CEOs are likely to produce higher quality disclosure than outsider CEOs. Using a sample of US firms from the S&P1500 index from 2001 to 2011, we hand‐collect whether a CEO is hired from inside the firm and, if so, the number of years they worked at the firm before becoming CEO. We then examine whether managers with more internal experience issue higher quality disclosures and offer three main findings. First, CEOs with more internal experience are more likely to issue voluntary earnings forecasts than those managers with less internal experience as well as those managers hired from outside the firm. Second, CEOs with more internal experience issue more accurate earnings forecasts than those managers with less internal experience as well as those managers hired from outside the firm. Finally, investors react more strongly to forecasts issued by insider CEOs than to those issued by outsider CEOs. In additional analysis, we find no evidence that these results extend to mandatory reporting quality (i.e., accruals quality, restatements, or internal control weaknesses), perhaps because mandatory disclosure is subjected to heavy oversight by the board of directors, auditors, and regulators. Overall, our findings suggest that when managers have work experience with the firm prior to becoming the CEO, the firm's voluntary disclosure is of higher quality.     

Uncertainty,Control, and Karl Polanyi’s Protective Response

Post-Keynesian institutionalist economists like Wallace Peterson and John Kenneth Galbraith recognized that the impact of uncertainty on economic wellbeing depends in part on the degree of control people have over the sources and consequences of it. Given the inability of government and other large institutions to reduce uncertainty or to provide citizens with the ability to manage it, mediating structures are considered as an alternative means of promoting economic security. The article concludes by describing and evaluating several of these alternatives.     

Interventions in Markets with Adverse Selection: Implications for Discount Window Stigma

I study the implications for central bank discount window stigma of a workhorse model of adverse selection in financial markets. In the model, firms (banks) need to borrow to finance a productive project. There is limited liability and firms have private information about their ability to repay their debts, which gives rise to the possibility of adverse selection. The central bank can ameliorate the impact of adverse selection by lending to firms. Discount window borrowing is observable and it may be taken as a signal of firms' credit worthiness. Under some conditions, firms borrowing from the discount window may pay higher interest rates to borrow in the market, a phenomenon often associated with the presence of stigma. I discuss these and other outcomes in detail and what they suggest about the relevance of stigma as an empirical phenomenon.     

Pricing Defaultable Bonds Using a Lévy Jump‐Diffusion Model

This paper uses a reduced‐form approach to derive a closed‐form pricing formula for defaultable bonds. The authors specify the default hazard rate as an affine function of multiple variables which follow the Lévy jump‐diffusion processes. Because such specification allows greater flexibility in the generation of a valid probability of default, their pricing model should be more accurate than the valuation models in traditional studies, which ignore the jump effects. This paper also proposes a new method for estimating the parameters in a Lévy Jump‐diffusion process. The real data from the Taiwanese bond market are used to illustrate how their model can be applied in practical situations. The authors compare the pricing results for the influential variables with no jump effects, with jump magnitudes following the normal distribution, and with jump magnitudes following the gamma distribution. The results reveal that the predictive ability is the best for the model with the jump components. The valuation model shown in this paper should help portfolio managers more accurately price defaultable bonds and more effectively hedge their portfolio holdings.     

Costs and potential funding of expanded public pension coverage in Asia

Public pension burdens in most emerging Asian economies are still relatively small. However, there are a number of reasons to believe that they will increase markedly in the coming years. First, many Asian economies will face rapidly ageing populations, which will raise pension and other old‐age‐related spending dramatically. Second, as economies develop, political pressures to expand the coverage of public pensions and raise pension benefits will likely increase. The first objective of this paper is to identify the potential fiscal burden of public pensions in 23 emerging Asian economies, based on econometric models and forecasts of GDP and demographic trends. Using two different methodologies yields estimated increases in the average share of public pension expenditures in GDP of 1.0 percentage point and 3.6 percentage points by 2030 compared with current levels. We believe the latter estimate is more realistic. The second objective is to recommend policies to provide adequate funding for public pension needs, including enhancing the efficiency of social insurance programs, improving the balance of revenues and expenditures, implementing more explicit fiscal rules and frameworks, and establishing stronger fiscal surveillance at the national and regional levels.     

Re‐vitalizing money demand in the Euro area. Still valid at the zero‐lower bound

The analysis of monetary developments has always been a cornerstone of the ECB's monetary analysis and, thus, of its overall monetary policy strategy. In this respect, money demand models provide a framework for explaining monetary developments and assessing price stability over the medium term. It is a well‐documented fact in the literature that, when interest rates are at the zero‐lower bound, the analysis of money stocks become even more important for monetary policy. Therefore, this paper re‐investigates the stability properties of M3 demand in the euro area in the light of the recent economic crisis. A cointegration analysis is performed over the sample period 1983 Q1 and 2015 Q1 and leads to a well‐identified model comprising real money balances, income, the long‐term interest rate and the own rate of M3 holdings. The specification appears to be robust against the Lucas critique of a policy dependent parameter regime, in the sense that no signs of breaks can be found when interest rates reach the zero‐lower bound. Furthermore, deviations of M3 from its equilibrium level do not point to substantial inflation pressure at the end of the sample. Excess liquidity models turn out to outperform the autoregressive benchmark, as they deliver more accurate CPI inflation forecasts, especially at the longer horizons. The inclusion of unconventional monetary policy measures does not contradict these findings.