Heterogeneous Treatment Under Regression Discontinuity Design: Application to Female High School Enrolment

This paper undertakes a regression discontinuity (RD) framework with multiple cutoffs unlike typical RD setting where researchers normalize the score variable and pool all the observations. This paper explores this heterogeneity in the effect of Islamic mayor on female secular high schooling in Turkey using the multiple cutoff RD framework developed in Cattaneo et al. (2016). The presence of many parties in the 1994 municipality election in Turkey means that vote share of the strongest opponent party can vary substantially leading to different cutoffs. Meyersson (2014) finds that Islamic mayors of 1994 promoted female high schooling using a normalized and pooled RD framework, which averages the effect across all the different cutoffs. We extend his work by segregating the effect of Islamic mayor across different opponent party's vote shares. Our results suggest that the positive effect on female secular high school attainment was more pronounced in municipalities where the strongest opponent party was secular than where the opponent was conservative. This heterogeneity can be attributed to a policy change in 1999, which restricted religious high school graduates from entering universities.     

Peer Effects: Evidence from Secondary School Transition in England

We estimate the effect of peers' prior achievement on student progress in secondary school, using administrative data on four cohorts of students in England. Students leaving primary for secondary school experience a big change in their peer group and these changes vary randomly from cohort to cohort. We exploit this variation to identify the effect of new peers on student achievement. We show that peer quality on entry to secondary school has a significant effect on students' subsequent achievement at age 14. The effect sizes are relatively small and are linked to peers' family background and early age achievements.     

Regression Discontinuity Applications with Rounding Errors in the Running Variable

Many empirical applications of regression discontinuity (RD) models use a running variable that is rounded and hence discrete, e.g. age in years, or birth weight in ounces. This paper shows that standard RD estimation using a rounded discrete running variable leads to inconsistent estimates of treatment effects, even when the true functional form relating the outcome and the running variable is known and is correctly specified. This paper provides simple formulas to correct for this discretization bias. The proposed approach does not require instrumental variables, but instead uses information regarding the distribution of rounding errors, which is easily obtained and often close to uniform. Bounds can be obtained without knowing the distribution of the rounding error. The proposed approach is applied to estimate the effect of Medicare on insurance coverage in the USA, and to investigate the retirement‐consumption puzzle in China, utilizing the Chinese mandatory retirement policy. Copyright © 2014 John Wiley & Sons, Ltd.     

The Value of Secondary School Quality*

Improving the quality of state‐funded secondary school education has become a major policy aim in the UK. However, without a valuation of the social benefits derived from public provision of educational services, the rational evaluation of policy to this end is difficult. Utilizing the argument that dwellings near better schools command a price premium, this paper presents results from an empirical exercise aimed at providing such a social valuation of increased school quality. Using a large set of data for England, and an instrumental variable approach, results indicate an elasticity of dwelling purchase price with respect to exam performance by schools at around +0.05. One implication is that society would value a general increase of five percentage points in exam performance by about £450 million per annum.     

Incentive effects of social assistance: A regression discontinuity approach

Before 1989, childless social assistance recipients in Quebec under age 30 received much lower benefits than recipients over age 30. We use this sharp discontinuity in policy to estimate the effects of social assistance on various labour market outcomes using a regression discontinuity approach. We find strong evidence that more generous social assistance benefits reduce employment. The estimates exhibit little sensitivity to the degree of flexibility in the specification, and perform very well when we control for unobserved heterogeneity using a first difference specification. Finally, we show that commonly used difference-in-differences estimators may perform poorly with inappropriately chosen control groups.     

Regression discontinuity inference with specification error

A regression discontinuity (RD) research design is appropriate for program evaluation problems in which treatment status (or the probability of treatment) depends on whether an observed covariate exceeds a fixed threshold. In many applications the treatment-determining covariate is discrete. This makes it impossible to compare outcomes for observations “just above” and “just below” the treatment threshold, and requires the researcher to choose a functional form for the relationship between the treatment variable and the outcomes of interest. We propose a simple econometric procedure to account for uncertainty in the choice of functional form for RD designs with discrete support. In particular, we model deviations of the true regression function from a given approximating function—the specification errors—as random. Conventional standard errors ignore the group structure induced by specification errors and tend to overstate the precision of the estimated program impacts. The proposed inference procedure that allows for specification error also has a natural interpretation within a Bayesian framework.     

Enterprise Education: The Role of Head Teachers

In the UK there have been recent policy developments in enterprise education, following the Davies Report (2002). In Scotland there has been the launch of a comprehensive enterprise education programme, the Determined to Succeed Strategy (Scottish Executive, 2003) for all schools in Scotland. This Strategy represented the Executive’s response to a working party review of education and enterprise. The review, Determined to Succeed, 2002 represented a comprehensive overview of requirements in order to provide enterprise education in all schools in Scotland. The aim stated is to “take an innovative and experimental approach in developing key themes in the initiative around the professional development of teachers, the engagement of disengaged school students and the promotion of a focused and resource-intensive approach to Enterprise in Education” (Scottish Executive, 2004). This paper reviews developments in enterprise education and the role of Head Teachers and Deputy Head Teachers (school principals and vice-principals). It reports the findings from research conducted with a Leadership Academy, delivered by the Columba 1400 organisation, with Head and Deputy Head Teachers for the Scottish Executive and assesses their critical role in enterprise education.     

A fuzzy bi-level method for modeling age-specific migration

Modeling and forecasting international migration are significant research areas since migration forecasts are vital in decision making and policy design regarding economy, security, society, and resource allocation. The methods for modeling and forecasting migration rely on strict subjective or statistical assumptions which may not always be met. In addition, lack of a universally accepted definition of the term “migrant” and the ambiguities in data due to recording and collection systems result in inconsistencies and vagueness in migration modeling. Considering these, in this paper, a fuzzy bi-level age-specific migration modeling method is proposed. The bi-level structure embedded in the model makes use of the well-known Lee-Carter method as well as fuzzy regression, singular value decomposition technique, and hierarchical clustering to reflect the general characteristics of the country of concern together with the distinct emigration and immigration behaviors of the age groups. Bayesian time series models are fitted to the time-variant fuzzy parameters obtained through the proposed method to forecast future migration values. The proposed method is applied on female and male age-specific emigration and immigration counts of Finland for 1990–2010 period and Germany for 1995–2012 period, and the future values are forecasted for 2011–2025 and 2013–2025 respectively. The method is compared with an existing Bayesian approach and the numerical findings display that the proposed fuzzy method is superior to the existing one in modeling and forecasting age-specific migration values within significantly narrower prediction intervals.     

Alternative Assumptions to Identify LATE in Fuzzy Regression Discontinuity Designs

There exist two alternative assumptions to identify local average treatment effects (LATE) in fuzzy regression discontinuity (RD) designs: local independence (LI) and local smoothness (LS). Together with the usual LATE assumptions requiring existence of a first‐stage and treatment monotonicity, either of these two assumptions is sufficient to identify RD LATE. I discuss the practical (and testable) implications of these alternative assumptions, and show that weakening LI by LS might be empirically relevant. However, when LI does hold, there are some practical implications one may explore. Numerical and empirical examples are briefly presented.     

The “Bologna Process” and college enrollment decisions

We use survey data on high school graduates before and after the Italian reform of tertiary education implementing the “Bologna Process” to estimate its impact on college enrollment. Individuals leaving school after the reform have a probability of enrollment that is 15% higher compared to otherwise identical individuals. This increase is concentrated among individuals with good school performance and low parental background. We interpret this result as an indication of the existence of constraints – for good students from less advantaged households – on the optimal schooling decision. We also find a small negative impact of the reform on university drop-out.     

High school completion and future youth unemployment: new evidence from High School and Beyond

In this paper, I provide new evidence from High School and Beyond (HSB) on the effects of compulsory attendance on high school completion and future youth unemployment. I develop Bayesian estimation approaches to the simultaneous equation model with ordered probit and two‐limit censored regression and the bivariate duration model, accounting for the heterogeneity in returns to education and the nonlinearity in the effects of compulsory attendance. I find substantial variability in returns to education across schools and evidence of diminishing marginal effects of compulsory attendance on high school completion. The simulation results suggest that increasing the compulsory attendance age raises the probability of completing high school and reduces the proportion of time the individuals are unemployed. These effects are much more pronounced for disadvantaged students but less pronounced for advantaged students, suggesting the potential effects of compulsory attendance on reducing the inequality in education and employment. Copyright © 2005 John Wiley & Sons, Ltd.     

Valuing school quality using boundary discontinuities

Existing research shows that house prices respond to local school quality as measured by average test scores. However, higher test scores could signal higher academic value-added or higher ability, more sought-after intakes. In our research, we show that both school value-added and student prior achievement – linked to the background of children in schools – affect households’ demand for education. In order to identify these effects, we improve the boundary discontinuity regression methodology by matching identical properties across admissions authority boundaries; by allowing for boundary effects and spatial trends; by re-weighting our data towards transactions that are closest to district boundaries; by eliminating boundaries that coincide with major geographical features; and by submitting our estimates to a number of novel falsification tests. Our results survive this battery of tests and show that a one-standard deviation change in either school average value-added or prior achievement raises prices by around 3%.     

Low Wage Returns to Schooling in a Developing Country: Evidence from a Major Policy Reform in Turkey

In this paper, we estimate returns to schooling for young men and women in Turkey using the exogenous and substantial variation in schooling across birth cohorts brought about by the 1997 reform of compulsory schooling within a fuzzy regression discontinuity design. We estimate that the return from an extra year of schooling is about 7–8% for women and an imprecisely estimated 2–2.5% for men. The low level of the estimates for men contrasts starkly with those estimated for other developing countries. We identify several reasons why returns to schooling are low for men and why they are higher for women in our context. In particular, the policy alters the schooling distributions of men and women differently, thus the average causal effect puts a higher weight on the causal effect of schooling at higher grade levels for women than for men.     

Nowcasting China’s GDP Using a Bayesian Approach

Real time nowcasting is an assessment of current-quarter GDP from timely released economic and financial series before the GDP figure is disseminated. Providing a reliable current quarter nowcast in real time based on the most recently released economic and financial monthly data is crucial for central banks to make policy decisions and longer-term forecasting exercises. In this study, we use dynamic factor models to bridge monthly information with quarterly GDP and achieve reduction in the dimensionality of the monthly data. We develop a Bayesian approach to provide a way to deal with the unbalanced features of the dataset and to estimate latent common factors. We demonstrate the validity of our approach through simulation studies, and explore the applicability of our approach through an empirical study in nowcasting the China’s GDP using 117 monthly data series of several categories in the Chinese market. The simulation studies and empirical study indicate that our Bayesian approach may be a viable option for nowcasting the China’s GDP.     

Coordination and non-coordination risks of monetary and macroprudential authorities: A robust welfare analysis

This study compares a central bank’s leaning against the wind approach with a mix of monetary and macroprudential policies under parameter uncertainty in an estimated DSGE model with two financial frictions. We show that uncertainty of the economic environment is an essential constituent in properly designing macroprudential policy. Although coordination between monetary and macroprudential policies minimizes the policymakers’ Bayesian risk, coordination and non-coordination risks threaten the goals of both authorities. The former describes the situation where the authorities partly resign from implementing the monetary policy objectives to stabilize macroprudential risk. The latter is when conducting a non-coordinated macroprudential policy induces higher total Bayesian risk than when only the central bank minimizes the expected total welfare loss. The robust Bayesian macroeconomic rules show that when financial shocks shrink the banks’ or entrepreneurial net worth, a contractionary macroprudential policy should be combined with an expansionary monetary policy. However, if capital adequacy ratio or risk shocks strike the economy, such a conflict in macroeconomics policy instruments disappears, thus synchronizing both policies.     

Implications of variant efficiency measures for policy evaluations in UK higher education

Policy goals in UK higher education encourage the publicly funded universities to become more-specialised and larger in size without compromising output quality. Efficiency gains are expected to flow from this increased specialisation in accordance with universities’ comparative research and teaching strengths. Mergers to reap further gains from economies of scale are also being actively encouraged. Given this scenario, the paper investigates whether best-practice efficiency measurement based on data envelopment analysis (DEA) provides empirical support for the current policy goals. It also assesses whether such support is dependent on the specific type of efficiency measure used in the DEA modelling. This assessment finds that a selection of (nine) commonly used, variant efficiency measures generally support the current policy goals. The paper also uses the principal-agent framework to explore the issues involved in using computed DEA-based efficiency scores for policy evaluations and possible funding guidance in UK higher education. This highlights empirically how policy-makers and universities can have very different preferences about which efficiency measure is to be used for policy evaluations and possible funding guidance.     

The Causal Effect of Education on Wages Revisited*

This study estimates the return to education in Britain using two instrumental variable (IV) estimators: one exploits variation in schooling associated with early smoking, the other uses the raising of the school leaving age; both affect a sizeable proportion of the sample. Early smoking is found to be a strong and valid IV and unlike previous IV strategies uses variations in education at numerous points across the distributions of (i) education, and (ii) ability. Thus whilst still a ‘local average treatment effect’ the estimate is closer to the average effect of additional education, akin to least squares but corrected for endogeneity.     

DOES EDUCATION REALLY IMPROVE HEALTH? A META‐ANALYSIS

While numerous studies assess the relationship between education and health, no consensus has been reached on whether education really improves health. We perform a meta‐analysis of 4866 estimates gleaned from 99 published studies that examine the health effects of education. We find that the current literature suffers from moderate publication bias towards the positive effects of education on health. After correcting for publication bias with an array of sophisticated methods, we find that the overall effect size is practically zero, indicating that education generates no discernible benefits to health. The heterogeneity analysis by Bayesian Model Averaging (BMA) and Frequentist Model Averaging (FMA) reveals that the reported estimates can be largely explained by whether the econometric models control for endogeneity of education, the types of data and the differences in health measurements. Our results also suggest that education may not be an effective policy option for promoting population health.     

How oil price and exchange rate affect stock price in China using Bayesian Quantile_on_Quantile with GARCH approach

We revisit the links of real exchange rate, oil price and stock market price for China using Bayesian Multivariate Quantile_on_Quantile with GARCH approach over the period of September 14, 2001 to June 17, 2022 (a total of 4051 days). Results indicate both the links between stock price and oil price and between stock price and exchange rate varying under different combinations of quantiles. GARCH model also indicate that yesterday news and persistence measures varying with current conditional variance under different quantiles. We further estimate half-life of a shock to our whole markets and find out the half-life of a shock range from 0.415 to 4.015 days. Result not found in previous study. Our study has important policy implications for the investors, practitioners, and the government.     

FORMASY FOrecasting and Recruitment in MAnpower Systems

In this paper the tools are developed for forecasting and recruitment planning in a graded manpower system. Basic features of the presented approach are:
- the system contains several grades or job categories in which the employees stay for a certain time before being promoted or leaving the system,
- promotability and leaving rate for any employee depend on time spent in the job category and personal qualifications (like education, experience, age),
- recruitment is not necessarily restricted to the lowest level in the system,
- several planning aims and restrictions are allowed.
The approach is based on a generalized Markov model for the dynamic behaviour of an individual employee. A forecasting procedure and a recruitment-scheduling procedure are based on this Markov model.