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This study estimates the efficiency of 19 tertiary hospitals in Taiwan using a two-stage analysis of Data Envelopment Analysis (DEA) and TOBIT regression. It is a retrospective panel-data study and includes all the tertiary hospitals in Taiwan. The data were sourced from open information hospitals legally required to disclose to the National Health Insurance (NHI) Administration, Ministry of Health and Welfare. The variables, including five inputs (total hospital beds, total physicians, gross equipment, fixed assets net value, the rate of emergency transfer in-patient stay over 48 h) and six outputs (surplus or deficit of appropriation, length of stay, the total relative value units [RVUs] for outpatient services, total RVUs for inpatient services, self-pay income, modified EBITDA) were adopted into the Charnes, Cooper and Rhodes (CCR) and Banker, Charnes and Cooper (BCC) model. In the CCR model, the technical efficiency (TE) from 2015–2018 increases annually, and the average efficiency of all tertiary hospitals is 96.0%. In the BCC model, the highest pure technical efficiency (PTE) was in 2018 and the average efficiency of all medical centers is 99.1%. The average scale efficiency of all medical centers was 96.8% in the BBC model, meaning investment can be reduced by 3.2% and the current production level can be maintained with a fixed return to scale. Correlation coefficient analysis shows that all variables are correlated positively; the highest was the number of beds and the number of days in hospital (r = 0.988). The results show that TE in the CCR model was similar to PTE in the BCC model in four years. The difference analysis shows that more hospitals must improve regarding surplus or deficit of appropriation, modified EBITDA, and self-pay income. TOBIT regression reveals that the higher the bed-occupancy rate and turnover rate of fixed assets, the higher the TE; and the higher number of hospital beds per 100,000 people and turnover rate of fixed assets, the higher the PTE. DEA and TOBIT regression are used to analyze the other factors that affect medical center efficiency, and different categories of hospitals are chosen to assess whether different years or different types of medical centers affect operational performance. This study provides reference values for the improvable directions of relevant large hospitals’ inefficiency decision-making units through reference group analysis and slack variable analysis.

This paper provides a theoretical explanation and consistent empirical evidence for the increase in the contemporaneous correlation between returns and aggregate earnings as the return interval is lengthened. Consistent with intuition and with Easton, Harris, and Ohlson 1992, the analysis shows that aggregation over time renders the lag in accounting recognition relatively less important and thus improves the returns‐earnings R2. Interestingly, the analysis also reveals that aggregating earnings over longer periods increases the positive covariance between aggregate earnings and the accounting lag, which may further increase the R2. This positive covariance can lead to an earnings coefficient greater than one over some range of aggregation, which is consistent with the findings of Easton et al. that over the 10‐year interval the returns‐earnings regression slope coefficient is greater than one (1.7). The empirical results highlight the fact that the slope coefficient, which is greater than one and increasing with the interval, accounts for much of the increment to the returns‐earnings R2. In fact, constraining the slope coefficient to be one results in an R2 of 11 percent for the 10‐year interval, which is considerably lower than the R2 of 47 percent when the regression is unconstrained. Hence, the positive covariance between current earnings and the accounting lag, rather than the diminishing effect of the accounting lag, appears to be the dominant explanation for the observed high R2 over long intervals.

Contents: The conceptual framework -- Educational outcomes and their impact on labor market outcomes -- Employment outcomes and links to the broader economic context -- Conclusion : how education can improve labor market outcomes.

Improving access to productive employment is a key policy challenge, especially in low-income countries (LICs), where the only asset in abundance is labor. Building on ongoing research on earnings mobility, this study uses unusually rich longitudinal data from Ghana and Tanzania to identify engines of, and barriers to, earnings and earnings mobility. It examines the role of individual characteristics such as gender, age, and skills and characteristics of the job, but it also focuses on the role of job switches for example, moves into and out of self-employment. It zooms in particularly on the drivers of transitions between low-paying and high-paying jobs, and addresses questions such as whether being low paid is a transitory or permanent phenomenon, and whether it has a scarring effect on an individual's employment prospects. The extent to which earnings dynamics differ for women and young adults is also discussed in detail. The cross-country comparison of earnings dynamics and labor market transitions helps shed light on the institutional factors that promote labor market mobility and entrepreneurship. The report is organized as follows: chapter one gives introduction. Chapter two presents a brief review of related literature. Chapter three gives a descriptive overview of the labor markets in the two countries. Chapter four examines the determinants of earnings levels. Chapter five examines determinants of earnings growth. Chapter six focuses on low-pay and high-pay transitions and analyzes whether the experience of being in a low-paying job undermines an individual's future earnings prospects. Chapter seven discusses key policy implications.

The World Bank Group promotes small and medium-size enterprise (SME) growth through both systemic and targeted interventions. A critical challenge is to root the many activities now undertaken in this broad space in a clear understanding of the characteristics and dynamics of SMEs role in the broader economy; and their actual and potential contribution to jobs, growth, and shared prosperity. A closely related challenge is to formulate clear strategies that connect interventions to intended outcomes and are accompanied by solid measurement systems that provide evidence of results and allow learning. Targeting means focusing benefits on one size-class of firms to the exclusion of others. Targeted support for SMEs is a big business for the World Bank Group, averaging around $3 billion a year in commitments, expenditures, and gross exposure over the 2006-12 periods. In the context of broader reforms, targeted small and medium-size enterprise (TSME) support can be a powerful tool and, given the size of the recent program, it is vital for the World Bank Group to use it effectively. Targeting SMEs is not an end in itself, but a means to create economies that can employ more people and create more opportunity for citizens to achieve prosperity. A thriving and growing SME sector is associated with rapidly growing economies. IEG s review of the SIP suggests that although it has high relevance, it is of doubtful efficacy and efficiency. MIGA s regular portfolio of TSME projects performs worse than other financial sector guarantees, and there is no evidence to determine their impact on SMEs. The viability and sustainability of SMEs investments, whether through SIP or the wholesale approach, could not be ascertained because of the lack of information on results and performance.

We develop a new quantile-based panel data framework to study the nature of income persistence and the transmission of income shocks to consumption. Log-earnings are the sum of a general Markovian persistent component and a transitory innovation. The persistence of past shocks to earnings is allowed to vary according to the size and sign of the current shock. Consumption is modeled as an age-dependent non-linear function of assets, unobservable tastes, and the two earnings components. We establish the nonparametric identification of the nonlinear earnings process and of the consumption policy rule. Exploiting the enhanced consumption and asset data in recent waves of the Panel Study of Income Dynamics, we find that the earnings process features nonlinear persistence and conditional skewness. We confirm these results using population register data from Norway. We then show that the impact of earnings shocks varies substantially across earnings histories, and that this nonlinearity drives heterogeneous consumption responses. The framework provides new empirical measures of partial insurance in which the transmission of income shocks to consumption varies systematically with assets, the level of the shock, and the history of past shocks.

Recent studies propose that limited investor attention causes market underreactions. This paper directly tests this explanation by measuring the information load faced by investors. The \"investor distraction hypothesis\" holds that extraneous news inhibits market reactions to relevant news. We find that the immediate price and volume reaction to a firm's earnings surprise is much weaker, and post-announcement drift much stronger, when a greater number of same-day earnings announcements are made by other firms. We evaluate the economic importance of distraction effects through a trading strategy, which yields substantial alphas. Industry-unrelated news and large earnings surprises have a stronger distracting effect.

This paper proposes a method to address the longstanding problem of lack of monotonicity in estimation of conditional and structural quantile functions, also known as the quantile crossing problem (Bassett and Koenker (1982)). The method consists in sorting or monotone rearranging the original estimated non-monotone curve into a monotone rearranged curve. We show that the rearranged curve is closer to the true quantile curve than the original curve in finite samples, establish a functional delta method for rearrangement-related operators, and derive functional limit theory for the entire rearranged curve and its functionals. We also establish validity of the bootstrap for estimating the limit law of the entire rearranged curve and its functionals. Our limit results are generic in that they apply to every estimator of a monotone function, provided that the estimator satisfies a functional central limit theorem and the function satisfies some smoothness conditions. Consequently, our results apply to estimation of other econometric functions with monotonicity restrictions, such as demand, production, distribution, and structural distribution functions. We illustrate the results with an application to estimation of structural distribution and quantile functions using data on Vietnam veteran status and earnings.

We analyze gender differences in expected starting salaries along the wage expectations distribution of prospective university students in Germany, using elicited beliefs about both own salaries and salaries for average other students in the same field. Unconditional and conditional quantile regressions show 5–15% lower wage expectations for females. At all percentiles considered, the gender gap is more pronounced in the distribution of expected own salary than in the distribution of wages expected for average other students. Decomposition results show that biased beliefs about the own earnings potential relative to others and about average salaries play a major role in explaining the gender gap in wage expectations for oneself.