Labor market dynamics over the business cycle: evidence from Markov switching models

This paper explores the evolution of the U.S. labor market across the business cycle and specifically the relationship between the unemployment rate and the average duration of unemployment. Labor market recoveries have long been thought of as lagging recoveries in broad economic activity. In particular, the unemployment rate peaks several months after official business cycle troughs and the average duration of unemployment lags further behind. Using estimates from Markov switching models of the unemployment rate, average duration of unemployment, jobless claims, and the exhaustion rate of regular unemployment insurance, this paper dates contractionary and expansionary phases of various aspects of the labor market and their relationship to the official phases of the business cycle. Evidence from these models suggests that inflows into unemployment recover almost contemporaneously with broad economic activity, while outflows recover almost a year after the end of official recessions. The differential timing in the recoveries of unemployment inflows and outflows, which is not a characteristic of most macro models of the labor market, accounts for the observed pattern between the unemployment rate and average duration of unemployment. Finally, when comparing the phases of the labor market to periods where Congress extends unemployment insurance benefits, it appears that policymakers target periods where the job finding rate is low, rather than periods where the stock of unemployed workers is high.     

Exploring the interaction between stock price index and exchange rates: an asymmetric threshold approach

This article examines the impact of stock market news on the foreign exchange markets of USA, Canada and UK, employing an innovative extension of the asymmetric threshold model of Apergis and Miller (2006). Under this framework we can disentangle the reaction of foreign exchange market to bad or good news and small or large news of stock returns. Our comprehensive daily data-set spans the period from January 1990 to June 2014. Using a cointegration and error correction model, we document the existence of a causal relationship between stock market and foreign exchange markets. Most interestingly, our results derived from the asymmetric threshold model confirm that the relationship between stock and foreign exchange markets is sensitive to short-term good or bad news and short-term small or large news. Our findings entail significant implications for policymakers, governments, risk managers and international investors.     

Asymmetric Linkages between BRICS Stock Returns and Country Risk Ratings: Evidence from Dynamic Panel Threshold Models

This study investigates the asymmetric linkages between the five BRICS (Brazil, Russia, India, China and South Africa) countries’ stock markets and three country risk ratings (financial, economic and political risk) in the presence of major global economic and financial factors. Using the dynamic panel threshold models, we find evidence of asymmetry in most cases. However, the significance and the signs of the effects of these risk ratings on the BRICS market returns differ across the lower and upper regimes. Furthermore, improvements in the global stock, West Texas Intermediate (WTI) and gold markets enhance the BRICS stock market performance. Increases in implied volatility indices lead to drops in the BRICS markets.     

Unemployment Invariance

Abstract. This paper provides a critique of the ‘unemployment invariance hypothesis’, according to which the behavior of the labor market, by itself, ensures that the long‐run unemployment rate is independent of the size of the capital stock, productivity and the labor force. In the context of an endogenous growth model, we show that the labor market alone need not contain all the equilibrating mechanisms to ensure unemployment invariance; in particular, other markets may perform part of the equilibrating process as well. By implication, policies that raise the growth path of capital or increase the effective working‐age population may influence the long‐run unemployment rate.     

Unemployment dynamics in emerging countries: Monetary policy and external shocks

This paper quantifies the impact of three key external shocks – external demand, interest rate, and uncertainty shocks – on emerging market economies (EMEs). We find that external shocks have a sizeable impact on macroeconomic fluctuations in EMEs and that a considerable fraction of this impact is through the domestic stock market. A decrease in external demand and an increase in external interest rate and uncertainty lead to a higher unemployment rate, lower stock market return, and a depreciation of the domestic currency. The EMEs' monetary policy actively responds to external shocks and dampens their impact on domestic activity.     

The impact of large-scale asset purchases on the S&P 500 index,long-term interest rates and unemployment

After the bankruptcy of Lehman Brothers in September 2008 and the financial panic that ensued, the Federal Reserve moved rapidly to reduce the federal funds rate to .25%. It was quickly judged that additional measures were needed to stabilize the US economy. Beginning in December 2008, the Federal Reserve Bank initiated three rounds of unconventional monetary policies known as quantitative easing (QE). These policies were intended to reduce long-term interest rates when the short-term federal funds rates had reached the zero lower bound and could not become negative. It was argued that the lowering of longer-term interest rates would help the stock market and thus the wealth of consumers. This article carefully investigates three hypotheses: QE impacting long-term interest rates, QE impacting the stock market and QE impacting unemployment using a Markov regime switching methodology. We conclude that QE has contributed significantly to increases in the stock market but less significantly to long-term interest rate and unemployment.     

Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach

This paper presents a capital asset pricing model‐based threshold quantile regression model with a generalized autoregressive conditional heteroscedastic specification to examine relations between excess stock returns and “abnormal trading volume”. We employ an adaptive Bayesian Markov chain Monte Carlo method with asymmetric Laplace distribution to study six daily Dow Jones Industrial stocks. The proposed model captures asymmetric risk through market beta and volume coefficients, which change discretely between regimes. Moreover, they are driven by market information and various quantile levels. This study finds that abnormal volume has significantly negative effects on excess stock returns under low quantile levels; however, there are significantly positive effects under high quantile levels. The evidence indicates that each market beta varies with different quantile levels, capturing different states of market conditions.     

The Choice of Technology and Equilibrium Wage Rigidity

In this general equilibrium model, firms engage in oligopolistic competition and choose increasing returns technologies to maximize profits. Capital and labor are the two factors of production. The existence of efficiency wages leads to unemployment. The model is able to explain some interesting observations of the labor market. First, even though there is neither long-term labor contract nor costs of wage adjustment, wage rigidity is an equilibrium phenomenon: an increase in the exogenous job separation rate, the size of the population, the cost of exerting effort, and the probability that shirking is detected will not change the equilibrium wage rate. Second, the equilibrium wage rate increases with the level of capital stock. Third, a higher level of capital stock does not necessarily reduce the unemployment rate. That is, there is no monotonic relationship between capital accumulation and the unemployment rate.     

The nonlinear time series properties of unemployment rates: some further evidence

The time series properties of unemployment rates for Germany, Japan, the UK and the US are re-examined. Evidence of nonlinear structure in the residuals of the most parsimonious linear ARMA models is reported for all countries except Japan. Modelling this nonlinearity using SETAR models suggests strong asymmetry in unemployment dynamics and the presence of a possible limit cycle for the UK. However, residual diagnostics for these models indicate remaining structure. Alternative TAR models conditioned on past growth rates of industrial production yield substantial reductions in residual variance over both linear and SETAR counterparts, iid residuals in all cases other than the US, and threshold values at or very near zero, clearly identifying the asymmetric behaviour of unemployment during expansionary and contractionary phases of the business cycle.     

Explaining House Prices in Australia: 1970–2003*

This paper aims to explain changes in real house prices in Australia from 1970 to 2003. We develop and estimate a long-run equilibrium model that shows the real long-run economic determinants of house prices and a short-run asymmetric error correction model to represent house price changes in the short run. We find that, in the long run, real house prices are determined significantly and positively by real disposable income and the consumer price index. They are also determined significantly and negatively by the unemployment rate, real mortgage rates, equity prices and the housing stock. Employing our short-run asymmetric error correction model, we find that there are significant lags in adjustment to equilibrium. When real house prices are rising at more than 2 per cent per annum, the housing market adjusts to equilibrium in approximately four quarters. When real house prices are static or falling, the adjustment process takes six quarters.     

Monetary shocks and asymmetric effects in an emerging stock market: The case of China

In this paper, we study the effect of monetary shocks on the Chinese stock market over the period of 2005 to 2011 with the MSVAR–EGARCH model. The evidence suggests that Chinese monetary policies have significantly asymmetric effects on the stock market in different time periods and market cycles. The effects of shocks from interest rate and reserve rate vary across market cycles but effects from money supply and exchange rate do not. Empirical evidence from the non-linear model shows that monetary policy changes increase stock market volatility, even though these monetary policies are often aimed at stabilizing macro-economic activities. The evidence suggests that both the market conditions and the effects on stock markets should be taken into consideration in monetary policy design and implementation.     

Monetary policy effectiveness and stock market cycles in ASEAN-5

This article examines the asymmetric effects of monetary policy on real output in bull and bear phases of stock market in five ASEAN economies (Malaysia, Singapore, Indonesia, the Philippines and Thailand) using the recently developed pooled mean group (PMG) technique. Stock market cycles are identified by employing Markov switching models and the rule-based nonparametric approach. Estimating the models using monthly data from 1991:1 to 2011:12, the results show that monetary policy (measured by short-term interest rate) has a negative and statistically significant long-run effect on real output in bull and bear market periods while the effects are stronger in bear periods than bulls. In the short run, there is no statistically significant relationship between monetary policy and real output. These results are consistent with finance constraints (capital market imperfection) models that predict that monetary policy is more effective during bear periods than bulls.     

A new approach to bad news effects on volatility: the multiple-sign-volume sensitive regime EGARCH model (MSV-EGARCH)

In this paper, using daily data for six major international stock market indexes and a modified EGARCH specification, the links between stock market returns, volatility and trading volume are investigated in a new nonlinear conditional variance framework with multiple regimes and volume effects. Volatility forecast comparisons, using the Harvey-Newbold test for multiple forecasts encompassing, seem to demonstrate that the MSV-EGARCH complex threshold structure is able to correctly fit GARCH-type dynamics of the series under study and dominates competing standard asymmetric models in several of the considered stock indexes.

Asymmetric labour force participation decisions

This article finds compelling evidence of asymmetric labour force participation decisions across demographic groups in response to changes in labour market conditions. This behaviour is consistent with predictions from the standard labour-leisure choice model and suggests that asymmetry in individual behaviour plays some role in the observed asymmetry of the aggregate unemployment rate. It is estimated that the weighted average difference in response to a one percentage point change in unemployment rates is sizeable when compared to the average monthly change in the aggregate labour force.     

Modeling the Taiwan Stock Market and International Linkages

This paper analyzes the Taiwan stock market and examines its price and volatility linkages with those of the United States. In particular, it tests the hypothesis that the short-term volatility and price changes spill over from the developed markets, mainly the United States, to the emerging Taiwan stock market. The model and the test are built upon Engle's ARCH (autoregressive conditional heteroskedasticity) and Engle and Kroner's M-GARCH (multivariate generalized ARCH) models. The paper differs from previous studies on the Taiwan stock market in three respects. First, instead of using daily closing prices, it uses close-to-open and open-to-close returns to avoid the problem of overlapping samples. It carefully models the day-of-the-week effect in daily data to avoid misspecification of the model. Second, to circumvent the generated regressor problem arising from the two-step estimation procedure, it also employs the M-GARCH model where all parameters are estimated simultaneously. Third, the misspecification test is carried out on various kinds of asymmetric ARCH factors. A substantial volatility spillover effect is found from the US stock market to the Taiwan stock market, especially for the model using close-to-open returns. There is also evidence supporting a spillover effect in price changes. The findings can be explained by the recent gradual opening of the Taiwan stock market to foreign investors.     

The labor wedge as a matching friction

We use a search and matching model to decompose the labor wedge into three classes of labor market frictions and evaluate their role for the labor wedge and unemployment. We find that there is an asymmetric effect of labor market frictions on the labor wedge and unemployment. While the wedge is to a large extent explained by changes in matching efficiency, unemployment is accounted for by the combination of frictions to matching efficiency, job destruction and bargaining. If search and matching frictions give rise to the labor wedge, then it is relevant for explaining unemployment mainly through changes in matching efficiency.     

Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data

Recent advancements in technology have led to wide availability of high-frequency financial data. The aim of this paper is to study the behavior of the Indian stock market. In particular, we analyze the returns at 5 min interval from NSE using the index NIFTY and the stocks State Bank of India and Infosys. A non-parametric approach is taken to detect jumps in the return process. The analysis shows that index jumps relate very closely with the general market news and announcements while individual stock jumps are associated with company specific news. We find that volatility of the market is best captured by asymmetric power ARCH models.

     

WHAT AFFECTS EFFICIENCY IN LABOUR MARKET MATCHING AT DIFFERENT TERRITORIAL AGGREGATION LEVELS IN POLAND?

We analyse efficiency of a labour market matching process at different levels of territorial aggregation and in different time horizons. We apply a stochastic matching frontier to random, job queuing and stock‐flow models. We use data for Poland, a country with highly regionally diversified unemployment. We find that search and matching mechanisms significantly differ with territorial aggregation. Higher efficiency in small regions results from lower frictions. Larger regions enjoy better structural matching if only labour market participants have time to search. Different policy measures should be designed to improve labour market matching efficiency at different regional levels.     

Periodically collapsing bubbles in the US stock market?

The existence of periodically collapsing bubbles in stock markets, applying the Enders–Siklos momentum threshold autoregressive (MTAR) model, is empirically investigated in this paper. Using this nonlinear time series technique, we are now able to analyse bubble-driven run-ups in stock prices followed by a crash in a cointegration framework with asymmetric adjustment. Therefore, applying this technique makes possible a deeper insight into the behavior of stock prices than was previously possible using conventional cointegration tests. Although the results from the subsample 1871–1995 cannot be interpreted in favor of the existence of periodically collapsing bubbles in the US stock market, the findings from the 1871–2001 sample period indicate their presence.     

An Evaluation of Inertia Models of Unemployment

Two approaches have been used to model unemployment. The first, conventional, approach involves linking the unemployment outcome to observed indices of productivity, structural factors and discrimination such as educational attainment, location and birthplace. The second approach, the inertia model, involves using a person's labour market history as a way of including in unemployment models information on the 'unobservables' that influence employability. This paper evaluates the performance of both models of unemployment. The results provide unambiguous support for the inertia model when modelling unemployment. The inertia model has higher explanatory power, higher within-sample prediction rate success and fewer out-of-sample forecasting errors than the conventional model. The estimates from the inertia model can be used to provide quite accurate predictions of the risk of becoming unemployed. This is important if individuals at high risk of becoming unemployed are to be targeted for labour market assistance.