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The “public interest” of financial institutions was used as an argument to intervene in accounting practices. The Bank of Spain's standard was not compatible with International Accounting Standard (henceforth IAS) 39 and the Spanish banking sector had become one of the most provisioned in Europe. This makes it an interesting case study of the relationship between provisioning and income smoothing. The 2008 financial crisis revealed that provisions were insufficient and a reinforcement regulation process began in 2012. This paper aims to examine whether, since 2012, the Bank of Spain's regulatory effort on impairment accounting standards has induced less income smoothing, correcting its countercyclical effect.

A regression model is applied during the period 2005–2020, to test whether there is a trend change in the correlation between the level of provisions and annual earnings in 2012.

The results show that from 2012 onwards (when the Bank of Spain reinforced the regulation on provisioning), there was a correction in income smoothing behaviour.

This study provides empirical evidence that reinforces the claim that accounting policy can affect decision-making accounting practices, in this particular case, at the Bank of Spain.

As a financial policy, dividend policy significantly affects firm value. This chapter analyzes how stock prices react to dividend decisions. First, a dividend payment is an extraction of value; therefore, stock price theoretically drops by the dividend amount on the ex-dividend day. In practice, the price drop and the dividend magnitude are not equal because of tax clientele, short-term trading, and market microstructure. Investors are indifferent in trading stocks before and after stocks go ex-dividend if they obtain equal marginal benefits from the two trading times. The difference in tax rates on dividends and capital gains leads to the gap between the price drop and the dividend amount. Moreover, if transaction costs are considerable, investors have high incentives to short-sell stocks until they cannot obtain more profits. The final outcome of this short-term trading is the difference between the price drop and the dividend amount. Furthermore, market microstructure factors such as limit orders, bid-ask spread, and price discreteness also create this gap. Second, dividend announcements convey valuable information to outsiders. When firms announce increases (decreases) in dividends, their stock prices tend to increase (decrease). Third, dividend policy is negatively related to stock price volatility. This negative relationship is explained by duration effect, rate of return effect, arbitrage realization effect, and information effect. Empirical evidence for this relationship is found in many countries. Finally, dividend smoothing is also considered as a signal about firms' future earnings. Consequently, firms with stable dividends have higher market value. In other words, dividend stability has a positive effect on stock prices.

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

Research shows that having student loan debt in retirement is associated negatively with life satisfaction, suggesting that student debt is a bane of retiree well-being. The rationale for this study is to determine the factors related to owing student debt in retirement, given the adverse effects on the well-being of retired households.

The study utilizes pooled cross-sectional data from the 2015 and 2018 U.S. National Financial Capability Study. The empirical analysis uses a sample of retired Americans aged 65 years and older (N = approximately 8,000) and estimates two-block logistic regression models to examine the effects of demographic, socioeconomic and behavioral factors on student loan indebtedness in retirement. A sensitivity analysis is performed for the subsample of retirees holding student debt for their children's education. Statistical interpretations use odds ratios.

The findings indicate that financial literacy, age, homeownership and high subjective financial knowledge are associated with a low likelihood of holding student loan debt in retirement. However, being Black, having postsecondary education, having difficulty covering expenses, having financially dependent children, having high-risk preferences and spending more than income increase the likelihood of holding student debt in retirement. The ensuing discussion will assist financial planners and educators identify practical ways to shape decisions regarding student loan debt in retirement.

The amount of student loan debt is unavailable in the dataset for analysis. One cannot infer causal relations from the study. The factors examined do not reflect the time the student loan was obtained.

The study focuses on the determinants of student loan indebtedness among retired Americans rather than young adults or older adults on the verge of retirement. The paper enhances the understanding of student loan holdings in the decumulation phase of the life cycle. Many US individuals have low retirement savings from which they draw a retirement income. The more the student debt burdens on retired Americans, the greater the likelihood of outliving their resources and experiencing poverty.

The traditional predictor of technical inefficiency proposed by Jondrow, Lovell, Materov, and Schmidt (1982) is a conditional expectation. This chapter explores whether, and by how much, the predictor can be improved by using auxiliary information in the conditioning set. It considers two types of stochastic frontier models. The first type is a panel data model where composed errors from past and future time periods contain information about contemporaneous technical inefficiency. The second type is when the stochastic frontier model is augmented by input ratio equations in which allocative inefficiency is correlated with technical inefficiency. Compared to the standard kernel-smoothing estimator, a newer estimator based on a local linear random forest helps mitigate the curse of dimensionality when the conditioning set is large. Besides numerous simulations, there is an illustrative empirical example.

Today, the increasing use of fossil fuels, energy security, concerns and the great importance of achieving sustainable economic growth underscore the urgent need to transition to a green energy system as soon as possible. To shed light on the relationship between the economy and renewable energy, this study assesses the nonlinear relationship between renewable energy consumption and economic growth for 24 OECD countries between 1990 and 2015.

The authors apply two nonlinear models: panel threshold regression (PTR) and panel smooth transition regression (PSTR).

The results show that the positive effect of renewable energy consumption on economic growth is conditional. On the one hand, the results of the nonlinear PTR model yielded a threshold value for renewable energy consumption of about 251.17. Below this threshold, the authors find a negative impact of renewable energy consumption on economic growth. However, above this threshold, renewable energy consumption becomes a favorable source of economic growth. Using the nonlinear PSTR model based on the gamma transition parameter of 2.014, the transition from low renewable energy consumption regime to higher is abrupt.

Referring to previous studies analyzing linear causality between renewable energy and economic growth, most of the results show various mixed and non-stable effects over the study period. The contributions of this study consist in conduct a series of empirical tests of the nonlinear effects of renewable energy use on economic growth using two nonlinear approaches such as the PTR and PSTR models. If the authors show that such a relationship is nonlinear, it is essential to check whether the transition from one weak regime to another strong regime is abrupt or smooth, using the PSTR approach.

The direct nexus between board characteristics, earnings management (EM) practices and dividend payout is examined in this study, followed by an examination of the indirect mediation impact of EM practices in the nexus between board characteristics and dividend payout. It aims to provide new empirical evidence from the Jordanian market, which is an emerging market.

The study population consists of all service firms that were listed on the Amman Stock Exchange (ASE) between 2012 and 2019. Due to the lack of availability of their complete data during the period, four service firms were omitted from the population; hence, a sample of 43 service firms was acquired over the time frame (2012–2019), yielding a total of 344 firm-year observations. Moreover, panel data analysis was employed in this study, and data for the study were acquired from yearly reports as well as the ASE's database.

Based on the GMM estimator findings, board size and independence have a negative and significant influence on the EM, but CEO/chairman duality has a positive and significant impact. Simultaneously, the impacts of female representation on the board of directors and the number of board meetings were both positive but insignificant. The findings also found that four board characteristics, including board size, female representation on the board of directors, CEO/chairman duality and the number of board meetings, had a significant negative or positive effect on dividend payout, while board independence did not. Additional findings show that EM practices have a direct negative insignificant effect on dividend payout, whereas EM practices partially mediate the relationship between board characteristics and dividend payout.

The current study's limitation is that it only searched in Jordanian service firms listed on ASE from 2012 to 2019 to fulfill the study's objectives; thus, we urge that future work explores the study models for other sectors, whether in Jordan or other growing markets such as the Middle East and North Africa.

The findings of this study may be utilized by analysts, investors and other strategic decision-makers to enhance Jordan's financial market's efficiency and efficacy. These findings will improve policymakers' willingness to impose appropriate constraints, perhaps boosting Jordan's financial market performance and efficacy. These findings may also help investors make more enlightened judgments by utilizing board characteristics and EM factors that predict firm dividend policy.

Contradictions in the results of earlier investigations inspired the current study, with the findings filling a gap in the existing literature. This study differs from previous studies by constructing a novel research model and analyzing the mediating influence of EM in the nexus between board characteristics and dividend payout.