Transitory Components Research Articles

Exercise Addiction Stability and Health Effects. A 6-Month Follow-up Postcompetition Study in Amateur Endurance Cyclists

To study the longitudinal stability of exercise addiction and its health effects in apparently healthy amateur endurance cyclists from pre- to 6-month post-competition. In total, 330 (30 women) adult cyclists were divided into 4 groups based on scores on the Exercise Addiction Inventory at both periods: nonrisk (n=262, 79.1%), transient (n=35, 10.6%), emerging (n=14, 4.2%) and persistent (n=20, 6.1%). The prevalence of high-risk exercise addiction was reduced postcompetition (16.7% vs 10.3%, P = 0.017). Of the cyclists with a high precompetition risk of exercise addiction, 63.6% (35/55) had a transient addiction associated with favorable effects on mental quality of life (effect size [ES]=0.52, 95% confidence interval: [0.20, 0.86]) and sleep quality (ES=-0.50 [-0.89, -0.12]) and avoided the worsening of depression symptom severity compared to the remaining groups (ES range=0.51-0.65). The 5.1% (14/275) of cyclists with a precompetition low risk of exercise addiction presented emerging exercise addiction that was associated with a worsened mental quality of life compared to the remaining groups (ES ranged 0.59-0.91), sleep quality compared to the nonrisk (ES=-0.56 [-0.02, -1.10]) and transient (ES=-0.72 [-1.36, -0.08]) groups and anxiety symptom severity compared to the persistent group (ES=0.51 [1.20,-0.19]). Exercise addiction had a marked transitory component at 6-month postcompetition with associated health benefits in amateur endurance cyclists.

Permanent inequality versus earnings instability and transmission of income shocks to consumption expenditure in India

The economic inequality in India has increased in the past years, and this increase is related to the changes in the covariance structure. Using the CMIE data for the 18 waves, this paper deals with the dynamic structure of earnings in India for the period of six years (2014–2019) by decomposing the covariance structures of earnings into the permanent and transitory/temporary components. For this, we have used eight different models to examine the earnings dynamics. The results based on these eight different models are different depending upon the specification of the model used. Nevertheless, all the models have some common characteristics. They show that both permanent and transitory components are significant in determining income inequality. The permanent component dominates the temporary component for most of the considered period, which means that the labour market is rigid. The individuals’ starting point determines their lifetime earning profile. It also implies that low-paid individuals will see lower incomes throughout their life. This paper further examines the transmission of income shocks to consumption, based on the association at lags of unexplained income and consumption expenditure growth. The covariance gives information about the effect of income shocks on expenditure if the measurement errors in income and measurement errors in expenditure are uncorrelated (orthogonal). Results show the covariance increases initially, reaches its peak in December 2016, then decreases and becomes flat.

Real Estate Investment Trusts and Commercial Property Markets in US

This article addresses the dynamic relationship between the commercial property market and the real estate investment trusts market at the aggregate and property levels by undertaking a co-integration analysis. The results suggest that there exists a common long-run co-integrating relationship between the commercial property and real estate investment trusts markets at the aggregate and property levels. Any disequilibrium in this long-run relationship between these markets is corrected by movement in the real estate investment trusts market. Further, to address the extent of movement in these variables as part of one co-integrated system into permanent and transitory components, we use the Kalman filter by conducting a state-space model. The results show that the cyclical component in the real estate trusts market is large at the aggregate and property levels, which are consistent with co-integrations results.

Identifying Transitory Components of Earnings

Identifying Transitory Components of Earnings

Disentangling Permanent and Transitory Monetary Shocks with a Nonlinear Taylor Rule

Abstract This article provides an estimation method to decompose monetary policy innovations into persistent and transitory components using the nonlinear Taylor rule proposed in Andolfatto, Hendry, and Moran (2008) [Are inflation expectations rational? Journal of Monetary Economics, 55, 406–422]. To use the Kalman filter as the optimal signal extraction technique, we use a convenient reformulation for the state equation by allowing expectations to play a significant role in explaining the future time evolution of monetary shocks. This alternative formulation allows us to perform the maximum likelihood estimation for all the parameters involved in the monetary policy as well as to recover conditional probabilities of regime change. Empirical evidence on the US monetary policy making is provided for the period covering 1986-Q1 to 2021-Q2. We compare our empirical estimates with those obtained based on the particle filter. While both procedures lead to similar quantitative and qualitative findings, our approach has much less computational cost.

Posterior Average Effects

Economists are often interested in estimating averages with respect to distributions of unobservables, such as moments of individual fixed-effects, or average partial effects in discrete choice models. For such quantities, we propose and study posterior average effects (PAE), where the average is computed conditional on the sample, in the spirit of empirical Bayes and shrinkage methods. While the usefulness of shrinkage for prediction is well-understood, a justification of posterior conditioning to estimate population averages is currently lacking. We show that PAE have minimum worst-case specification error under various forms of misspecification of the parametric distribution of unobservables. In addition, we introduce a measure of informativeness of the posterior conditioning, which quantifies the worst-case specification error of PAE relative to parametric model-based estimators. As illustrations, we report PAE estimates of distributions of neighborhood effects in the U.S., and of permanent and transitory components in a model of income dynamics.

Individual forecaster perceptions of the persistence of shocks to GDP

SummaryWe analyse individual professional forecasters' beliefs concerning the persistence of GDP shocks. Despite substantial apparent heterogeneity in perceptions, with around one half of the sample of professional forecasters believing shocks do not have permanent effects, we show that these apparent differences may be largely due to short samples and survey respondents being active at different times. When we control for these effects, using a bootstrap, we formally do not reject the null that individuals' long‐horizon expectations are interchangeable at a given point in time. When we apply the same bootstrap approach to their medium‐term expectations, we do reject the null. We explore this difference between long and medium‐horizon forecasts by decomposing revisions in forecasts into permanent and transitory components.

Forecasting Stock Price using LSTM-CNN Method

Foreseeing assumes an indispensable part in setting an exchanging methodology or deciding the ideal opportunity to purchase or sell stock. We propose an element combination long transient memory-convolutional neural organization (LSTM-CNN) model, which joins highlights gained from various presentations of similar information, i.e., stock timetable and stock outline pictures, to anticipate stock costs. The proposed model is created by LSTM and CNN, which extricate impermanent and picture components. We assessed the proposed single model (CNN and LSTM) utilizing SPDR S&P 500 ETF information. Our LSTM-CNN combination highlight model surpasses single models in foreseeing evaluating. Also, we track down that the candle graph is the most precise image of a stock diagram that you can use to anticipate costs. Subsequently, this examination shows that prescient mistake can be viably decreased by utilizing a blend of transitory and picture components from similar information as opposed to utilizing these provisions independently.

Stock Market Volatility and Recent Crises

We study the volatility of the US stock market and its sectors as defined by S&P before and after four recent crises: the Mexican crises, the Asian crises, the Dotcom crises and the Great Recession. We compare the increase in daily volatility with the increase in the implied daily volatility (derived from the monthly volatility) to determine if there was a lasting economic effect of each crisis or the increase in volatility was due to financial transitory components. We find that for each crisis the effect was different even though the increase in volatility was present for most of the crises in the post crises period. The paper helps investors and economic policy makers understand what the response to each crisis should be to stabilize the economy.

Time‐varying trend models for forecasting inflation in Australia

AbstractWe investigate whether a class of trend models, which decompose a time series into an underlying trend and transitory component, with various error term structures can improve upon the forecast performance of commonly used time series models when forecasting consumer price index (CPI) inflation in Australia. The main result is that trend models tend to provide more accurate point and density forecasts at medium to long forecasting horizons compared with conventional autoregressive and Phillips curve models. The best medium‐term point forecasts come from a trend model with stochastic volatility in the transitory component and that with a moving average component, whereas long‐run point forecasts are better made by trend models with stochastic volatilities and a moving average component. In a full sample study, we also find that trend models can capture various dynamics in periods of significance to the Australian economy which conventional models cannot. This includes the dramatic reduction in inflation when the RBA adopted inflation targeting, a one‐off 10% Goods and Services Tax inflationary episode in 2000, and then gradually decline in inflation since 2014.

The Relationship between Stock Price Index and Industrial Production Index in Construction Industry

This paper investigates the relation between stock price index and industrial production index in construction industry, namely, the relation between stock market and real economy activity. Because stock price is the leading indicator, stock price may be related to industrial production. Previous studies have been studied on the relation between released stock price index and IPI. However, this study is distinguishable in that released stock price index is decomposed into fundamental component and transitory component. The first step in this empirical analysis is to decompose released stock price index. In state-space model, fundamental component is set up as a random walk process and transitory component is modeled as a stationary AR(2) process. In the second step, to check the stationarity, the ADF unit root test is used. In the third step, to elucidate the relationship between stock price index and IPI, Granger causality test is applied. The findings are as follows. The results reveal that released stock price index Granger causes IPI. The fundamental component of stock price index Granger causes IPI, and the transitory component of stock price index Granger causes IPI. The increase in released stock price index and the fundamental component of stock price index causes IPI to increase after one month. This paper indicates that the analysis of stock price index helps to predict IPI in construction industry.

Anchoring of inflation expectations in large emerging economies

We investigate through a time-varying trend inflation model the anchoring of the inflation process in the five largest emerging economies: Brazil, Russia, India, China and South Africa (also known as the BRICS countries) since 1990s. Our analysis is based on a non-centered unobserved components stochastic volatility model of inflation. We decompose inflation into a permanent stochastic trend and a transitory (inflation gap) component. Monetary policy frameworks such as inflation targeting are designed to mainly anchor inflation expectations. By analyzing time-varying volatility of trend shocks, we measure changes in the degree of anchoring of inflation expectations over time. We find that after adoption of inflation targeting, reduction in the volatility of trend shocks is observed for all these economies. For all the BRICS economies except China, we find that the trend estimates were significantly close to the inflation target announced by the respective central banks. Results from the bayesian model comparison, show that the inflation process in these economies is conclusively time-varying. Hence by adding stochastic volatility we find a better fit for the inflation process.

Who’s Hit Hardest? The Persistence of the Employment Shock by the COVID-19 Crisis

The persistence of the employment shock by COVID-19 has various policy implications during the pandemic and beyond it. After evaluating the impact of the health crisis at the individual level, this study decomposes employment losses into persistent and transitory components using the observed timing of the three major outbreaks and subsequent lulls. The estimation results show that while face-to-face services were undoubtedly hit hard by the COVID-19 crisis, the sectoral shock was less persistent for temporary jobs and self-employment. Permanent jobs in the hard-hit sector showed increasingly large persistent losses through the recurring crises, indicating gradual changes in employer responses. The persistent job losses were concentrated on young and older workers in career transitions, whose losses are likely to have long-term effects. These results suggest that targeted measures to mitigate the persistent effects of the employment shock should take priority during the recovery process.

What Do Data on Millions of U.S. Workers Reveal About Lifecycle Earnings Dynamics?

We study individual male earnings dynamics over the life cycle using panel data on millions of U.S. workers. Using nonparametric methods, we first show that the distribution of earnings changes exhibits substantial deviations from lognormality, such as negative skewness and very high kurtosis. Further, the extent of these nonnormalities varies significantly with age and earnings level, peaking around age 50 and between the 70th and 90th percentiles of the earnings distribution. Second, we estimate nonparametric impulse response functions and find important asymmetries: Positive changes for high‐income individuals are quite transitory, whereas negative ones are very persistent; the opposite is true for low‐income individuals. Third, we turn to long‐run outcomes and find substantial heterogeneity in the cumulative growth rates of earnings and the total number of years individuals spend nonemployed between ages 25 and 55. Finally, by targeting these rich sets of moments, we estimate stochastic processes for earnings that range from the simple to the complex. Our preferred specification features normal mixture innovations to both persistent and transitory components and includes state‐dependent long‐term nonemployment shocks with a realization probability that varies with age and earnings.

Taking the 'Non' Out of Non-GAAP: Routine Non-GAAP Usage and Investor Pricing

Earnings are an important input for equity investors’ valuation decisions. Managers and analysts increasingly report non-GAAP earnings on an ongoing basis, routinely removing recurring items, such as amortization and stock-based compensation, from GAAP earnings. We document that by 2019, non-GAAP earnings were used in all prior eight quarters for 38 percent of firms. The routine use of non-GAAP earnings for the same firm quarter after quarter suggests that non-GAAP has become the “generally accepted” earnings measure for valuation purposes for a significant portion of publicly-traded firms. We provide evidence that routine non-GAAP usage allows investors to gain experience with non-GAAP earnings that facilitates their pricing of non-GAAP exclusions. Our findings point to a capital markets consequence of the shift from the traditional use of non-GAAP, in which adjustments are made for transitory earnings shocks, to the routine use of non-GAAP, in which adjustments are made for both recurring and transitory components of earnings.

Chronic poverty: What affects its level and severity?

The study focuses on the chronic or long-term poverty of the Russian population in the 2010s. To estimate the chronic poverty, Eurostat modified definition is applied. The level and factors of chronic poverty are estimated at the balanced panel data of the Russia Longitudinal Monitoring Survey subject to sample attrition effect. The main factors of falling into a long-term poverty trap are the presence of children, unemployment, living in rural areas, and frequent alcohol consumption. The risk of chronic poverty is lower if family members have tried to start their own business. The presence of retirement age persons in the family and children growing up reduce the risk of poverty. Extreme poverty, with all other things being equal, makes it harder for families to escape from chronic poverty. The main factors of chronic poverty severity are similar to those of chronic poverty. Some differences in the effects on chronic and transitory components of poverty severity are identified. It is noted that the increase in the coverage of the chronic poor with multiple deprivations by the conditional cash transfer program with the extended period of support and the increased assistance granted to these persons could contribute to the chronic poverty reduction.

Permanent and transitory effect of public debt on economic growth

PurposeThis study examines the effect of public debt on the economic growth of OECD countries by disentangling the effect into permanent and transitory components. The study covers 37 OECD countries.Design/methodology/approachThe Mundlak decomposition was employed to decompose the effect of public debt into its transitory and permanent effect on economic growth. To account for potential endogeneity problem, the Hausman and Taylor estimator was employed to estimate the decomposed model. Further, the study disaggregated the OECD model into country group models for further analysis of the dynamics of the relationship between the variables.FindingsThe findings of the study reveal that in the full OECD model public debt exerts a significant negative permanent and positive transitory effect on economic growth. This was robust to alternative model specifications. The magnitude of the negative permanent effect of debt was found to be larger than the positive transitory effect. Further, the estimates of the disaggregated models reveal that though public debt has a negative permanent effect across all the country groups, it was not the case for the transitory effect of debt. Also, a net public debt model was estimated, and its effect on public debt was found to be largely insignificant, exhibiting a Ricardian-like behaviour.Originality/valueTo the best of our knowledge, this is the first study, particularly in the OECD context that employed the Mundlak transformation to examine the permanent versus transitory effect of public debt on economic growth.

FASB was Right: Earnings Beat Cash Flows when Predicting Future Cash Flows

Do accruals-based accounting earnings provide better information to investors about future operating cash flows than operating cash flows themselves, as predicted by FASB’s conceptual framework? The most recent evidence (Nallareddy et al., 2020) is that operating cash flows, measured correctly using cash flow statement data, consistently outperform earnings. However this evidence compares operating cash flows with “bottom line” earnings, handicapping earnings by including non-operating and transitory components with no corresponding operating cash flow. Operating earnings consistently dominate operating cash flow’s predictive ability in a battery of tests, especially after addressing cross-sectional differences among firms.

Google Search Queries, Foreclosures, and House Prices

We study whether Google search behavior for “mortgage assistance” and “foreclosure help” aggregated in the mortgage default risk indicator (MDRI) of Chauvet et al. (2016) helps predict future house prices and foreclosures in local residential markets. Using a long-run equilibrium model, we disaggregate house prices into their fundamental and bubble components, and we find that MDRI dampens both components of house prices. This negative relationship is robust to various model specifications and time horizons. A higher intensity of search online, however, is associated with lower future foreclosure rates. We also find that foreclosure rates increase after a decline in the fundamental component of home values, but are not sensitive to their transitory (bubble) component. Foreclosure rates are higher in metropolitan areas located in non-recourse states. We interpret these findings as evidence for strategic household behavior. Our paper sheds new light on the predictive power of household sentiment derived from Google searches on prices and foreclosure rates in local housing markets.

Multivariate unobserved component model for an oil-exporting economy: the case of Russia

ABSTRACT This paper presents an unobserved component model for real GDP, real household consumption, and real investment of an oil-exporting economy. The model decomposes domestic variables’ dynamics into permanent and transitory components, accounting for dependence on oil prices in the short and long-run, as well as for the common long-run economic growth and the common cyclical behaviour. Estimated on the Russian macroeconomic variables, the model exhibits a strong dependence on oil prices.