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To predict the passenger volume reasonably and accurately, this paper fills the gap in the research of quarterly data forecast of railway passenger volume. The research results can also provide references for railway departments to plan railway operation lines reasonably and efficiently.

This paper intends to establish a seasonal cycle first order univariate grey model (GM(1,1) model) combing with a seasonal index. GM (1,1) is termed as the trend equation to fit the railway passenger volume in China from 2014 to 2018. The railway passenger volume in 2019 is used as the experimental data to verify the forecasting effect of the proposed model. The forecasting results of the seasonal cycle GM (1,1) model are compared with the traditional GM (1,1) model, seasonal grey model (SGM(1,1)), Seasonal Autoregressive Integrated Moving Average (SARIMA) model, moving average method and exponential smoothing method. Finally, the authors forecast the railway passenger volume from 2020 to 2022.

The quarterly data of national railway passenger volume have a clear tendency of cyclical fluctuations and show an annual growth trend. According to the comparison of the modeling results, the authors know that the seasonal cycle GM (1,1) model has the best prediction effect with the mean absolute percentage error of 1.32%. It is much better than the other models, reflecting the feasibility of the proposed model.

As the previous grey prediction model could not solve the series prediction problem with seasonal fluctuation, and there are few research studies on quarterly railway passenger volume forecasting, GM (1,1) model is taken as the trend equation and combined with the seasonal index to construct a combination forecasting model for accurate forecasting results in this study. Besides, considering the impact of the epidemic on passenger volume, the authors introduce a disturbance factor to deal with the forecasting results in 2020, making the modeling results more scientific, practical and referential.

This study aims to develop a high-quality impairment loss allowance model in conformity with Indonesian Financial Accounting Standards 71 (PSAK 71) that has significant contribution to national interests and the banking industry.

The determination of the impairment loss allowance model is settled through 7 stages, using integration of some statistical methods such as Markov chain, exponential smoothing, time series analysis of behavioral inherent trends of probability of default, tail conditional expectation and Monte Carlo simulation.

The model which is developed by the authors is proven to be a high-quality and reliable model. By using the model, it can be shown that the implementation of the expected credit losses model on Indonesian Financial Accounting Standards 71 is more prudent than the implementation of the incurred loss model on Indonesian Financial Accounting Standards 55.

Determination of defaults was based on days past due, and the analysis in this study did not touch the aspects of hedge accounting in general.

This developed model will contribute significantly to national interests as a source of reference for other banks operating in Indonesia in calculating impairment loss allowance (CKPN) and can be used by the Financial Services Authority of Indonesia (OJK) as a guideline in assessing the formation of impairment loss allowance for banks operating in Indonesia.

As so far there is not yet an available standardized model for calculating impairment loss allowance on the basis of Indonesian Financial Accounting Standards 71, the model developed by the authors will be a new breakthrough in Indonesia.

There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.

The purpose of this paper is to investigate whether income smoothing does indeed improve the informativeness of stock prices about firms' future earnings and cash flows. Also an approach to studying the effects of income smoothing is presented.

This study uses data from 1992‐2006 and runs regressions on each of the 560 industry‐year cross‐sections. The data compiled from the financial statements of firms were collected for each year available from the Tehran Stock Exchange database. Income smoothing is defined as the management of accruals to reduce time‐series variation in income, and uses a cross‐sectional version of the Jones model, modified by Kothari, Leone and Wasley. Smoothing is measured as the variation of net income relative to the variation in CFO, or the correlation between changes in accruals and changes in CFO. Informativeness is measured as the coefficient on future earnings (cash flows) in a regression of current stock return against current and future earnings (cash flows and accruals).

The findings suggest that income smoothing enhances the information content of the effect of stock price on future earnings, thus improving the ability of market participants to make informed decisions about the allocation of capital resources.

Although previous research on the subject of income smoothing in an emerging market has been documented, its effect on stock prices efficiency is largely unknown. Thus, this paper presents an approach to studying the effects of income smoothing and the knowledge that the ability to manage earnings could improve stock prices efficiency could be useful for academics and policymakers in this market.

This paper aims to study the effect of corrugated skins on the aerodynamic performance of the cambered NACA 0012 airfoils at different corrugations parameters, maximum cambers, Reynolds numbers and maximum camber locations.

In this work, numerical approach is concerned, and results are obtained based on the finite volume approach. To characterize the effect of corrugated skins, the NACA 0012-corrugated airfoil section is chosen as the base airfoil, and different cambered corrugated airfoil sections are obtained by inclusion the camber to the base airfoil. In this research, the corrugation shape is a sinusoidal wave and corrugated skins are in the aft 30 per cent of airfoil chord. To investigate the effect of corrugations on the cambered sections, the drag coefficient and averaged lift curve slope for the corrugated airfoils are compared to those of the corresponding smooth sections.

Results indicate that the effect of increase in the maximum camber and also Reynolds number on the relative zero-incidence drag coefficient is of little importance at low corrugation amplitudes, whereas at high corrugation, amplitude results in different behaviors. It is found that as the maximum camber increases, the deterioration in the relative curve slope introduced by corrugated skins is reduced, and reduction in this deterioration is significant for high corrugation amplitudes airfoils. It is shown that an increase in the maximum camber location has nearly no effect on the relative zero-incidence drag coefficient and also relative lift curve slope.

The outcome of the present research provides the clues for better understanding of the effect of different corrugations parameters on the aerodynamic performance of the unmanned air vehicles to have as high aerodynamic performance as possible in different mission profiles of such vehicles.

The purpose of this paper is to investigate whether income smoothing helps to reduce volatility in reported earnings and which firms are more inclined to be engaged in income smoothing.

The authors used negative correlation between pre-managed earnings of a firm and its discretionary accruals (DAs) as proxy for income smoothing and the firms having more negative correlation coefficient are expected to have lower volatility in their reported earnings. The authors used Kothari et al.’s (2005) version of modified-Jones model to estimate DAs and used least squares estimations to investigate the research questions using six-year (2007-2012) sample of non-financial firms listed over Karachi Stock Exchange, Pakistan.

The authors found that firms experiencing more volatility in economic activities and smaller firms are more aggressively involved in income smoothing. Moreover, a predominant majority (72.2 per cent) of firms in the sample are involved in income smoothing through accruals manipulation. Also, the authors found that firms which are more aggressively involved in income smoothing have lesser volatility in reported earnings. Lastly, the level of DAs per se does not have any impact on income smoothing.

The proxy used for income smoothing, though the authors consider it to be better, is not the only one used in literature and the sample is limited to Pakistan.

This study adds to earnings management literature by providing evidence on extensive accrual manipulation for income smoothing in Pakistan.

The purpose of this paper is to examine the determinants of the use of loan loss provisions (LLPs) to smooth income by banks in South Africa. More specifically, the authors examine the influence of ownership, IFRS disclosure rules and economic fluctuation on the income smoothing behaviour of South African banks while controlling for the traditional determinants of bank income smoothing via LLPs.

The study employs fixed effect regression methodology to estimate the determinants of discretionary LLPs.

The authors find that South African banks do not use LLPs to smooth income when they are: under-capitalised, have large non-performing loans and have a moderate ownership concentration. On the other hand, income smoothing is pronounced when South African banks are rather more profitable during economic boom periods, well-capitalised during boom periods and is pronounced among banks that adopt IFRS and among banks with a Big 4 auditor. The authors also find that banks use LLPs for capital management purposes, and bank provisioning is procyclical with economic fluctuations.

Bank supervisors in South Africa should monitor the bank provisioning practices in South Africa closely to ensure that LLPs are not used as a substitute for bank capital. Banks in South Africa should not use sufficient provisioning as a substitute for sufficient bank capital. Second, the evidence for procyclical bank provisioning shows that provisioning by South African banks reinforce the current state of the economy and might compel bank supervisors in South Africa to consider the adoption of a dynamic provisioning system that is already adopted by bank supervisors in Spain, Peru, Uruguay, Colombia and Bolivia.

Bank income smoothing is an important issue because it has implications for banking stability and accounting transparency. There are few studies on bank income smoothing for emerging economies particularly in Africa where there are substantial differences in ownership and accounting rules. This is the first South African study to examine the influence of disclosure rules, ownership and economic cycle fluctuations on bank income smoothing behaviour via LLPs.

The purpose of this paper is to empirically examine whether the way African banks use loan loss provisions (LLP) to smooth earnings is influenced by capital market motivations and the type of auditor, after controlling for non-discretionary determinants of provisions and fluctuations in the business cycle.

To test the income smoothing hypothesis, the model was estimated using panel least square with White’s robust standard error correction, as well as, with and without period fixed effect.

The findings support the income smoothing hypothesis and indicate that African banks use LLP to smooth earnings; listed African banks use LLP to smooth earnings to a greater extent compared to non-listed African banks, possibly, for capital market reasons; income smoothing via LLP is not reduced among African banks with Big 4 auditors; and after controlling for macroeconomic fluctuation, there is evidence that bank provisioning is procyclical with fluctuations in the business cycle.

The findings have three implications. One, listed African banks smooth income because they are more visible to investors; investors do not view stock price fluctuations as a good signal. Securities market regulators in African countries should enforce strict disclosure rules that reduce earnings smoothing practices to improve the transparency of bank earnings in the region. Two, the presence of a Big 4 auditor did not improve the informativeness of LLP estimates among African banks. Three, the evidence for procyclical provisioning suggest the need for dynamic LLP system in Africa.

This paper is the first cross-country African study to investigate whether provisions-based income smoothing decreases with the presence of a Big 4 auditor. The findings indicate that this is not the case among African banks.

This paper seeks to investigate whether executive wealth sensitivity to stock price fluctuations serves as an incentive for earnings management.

Using a sample of 475 chief executive officers (CEOs) from 410 randomly selected Standard and Poor's (S&P) 1500 firms, the relation between executive stock‐based compensation, corporate governance, and earnings management is empirically examined.

CEO wealth sensitivity is positively associated with abnormal accrual usage and the relation is consistent with income‐smoothing. Also find that governance does not significantly influence the association between CEO stock‐based wealth sensitivity and earnings smoothing.

This study has several limitations. First, it is assumed that the accruals models used provide accurate measures of abnormal accruals. Several recent studies question the reliability of these models. Second, the wealth sensitivity measures in this paper are based on Black Scholes option pricing. A number of the assumptions underlying Black Scholes do not hold for executive options. Finally, governance factors that influence the examined relations may not be effectively captured by the measures in this paper.

The findings have implications for compensation design. Unintended consequences of high CEO exposure to firm‐specific risk may not be effectively mitigated by governance. These results also have potential policy implications. In the wake of recent accounting scandals regulators tightened governance standards for corporate. The findings suggest that reliance on these standards as deterrents to earnings management may not be warranted.

The study contributes to both the earnings management and corporate governance literatures. The results of this study suggest that CEO stock‐based wealth sensitivity is an earnings management incentive.

The work of Scott, Bruce and Cooper on small firm growth and development is reviewed. It is shown that by adapting exponential smoothing forecasting procedures it is possible to monitor the commercial health of a small firm. This is achieved by ‘tracking’ key indicators and producing an exception message when a signal exceeds certain predetermined control limits. The procedure is equally effective for either a step or ramp change in the underlying input data. This suggested approach requires little sophistication in either data or technique and has a practical application to small firm management, while adding to our understanding of the process of growth of small businesses.