This paper provides details on the sampling design, field results and nonresponse, as well as population adjustments for the 2018 Sample O of the Socio-Economic Panel (SOEP). Sample O refreshes the SOEPCore sample by adding the residents of households in neighborhoods that receive government...

In a randomized control trial, the precision of an average treatment effect estimator and the power of the corresponding t-test can be improved either by collecting data on additional individuals, or by collecting additional covariates that predict the outcome variable. To design the...

Using a case study approach, this research explores the various potential limiting factors of climate change adaptation, based on the experience of four low-lying islands in central Philippines. In the aftermath of the 2013 7.2-magnitude Bohol earthquake, the islands now become flooded even...

We examine whether and how democratic procedures can achieve socially desirable public good provision in the presence of profound uncertainty about the benefits of public goods, i.e., when citizens are able to identify the distribution of benefits only if they aggregate their private...

Despite of its relevance for science policy and the scientific community, empirical research on doctoral education in Germany is sparse. The few papers available face challenges in the sampling approach: simple random sampling is not possible, because a universal register of PhD candidates in...

Econometric analysis requires filtering techniques that are adapted to cater to data sequences that are short and that have strong trends. Whereas the economists have tended to conduct their analyses in the time domain, the engineers have emphasised the frequency domain. This paper places its...

To promote digital transformation, equal emphasis needs to be placed on digital skills development as to infrastructure development. Integral to investment in digital skills development is the subsequent management and evaluation of digital training programmes. This paper assesses mechanisms to...

Die Randomized-Response-Technik (RRT) ist ein neuartiges Befragungsverfahren für sensitive Merkmale. Bei ihrer Anwendung werden die Antworten irreversibel stochastisch verschlüsselt und somit geschützt. Aus den verschlüsselten Antworten lassen sich die Verteilungsparameter der untersuchten...

This study divides the households into five groups according to the electricity consumption and compares the characteristics and the determinants of household electricity consumption for only two groups, the lowest and the highest. The data are drawn from a household energy consumption sample...

We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss different objects of interest based on (1) local effects conditional on the control function, and (2) global effects obtained from...

Pseudo-panels allow estimation of panel models when only repeated cross-sections are available. This involves grouping individuals into cohorts and using the cohort means as if they are observations in a genuine panel. Their practical use is constrained by a lack of consensus on how the...

We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss different objects of interest based on (1) local effects conditional on the control function, and (2) global effects obtained from...

We develop a distribution regression model under endogenous sample selection. This model is a semiparametric generalization of the Heckman selection model that accommodates much rich patterns of heterogeneity in the selection process and effect of the covariates. The model applies to continuous,...

We introduce a mixed-frequency score-driven dynamic model for multiple time series where the score contributions from high-frequency variables are transformed by means of a mixed-data sampling weighting scheme. The resulting dynamic model delivers a flexible and easy-to-implement framework for...

We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...

We study the impact of manipulating the attention of a decision-maker who learns sequentially about a number of items before making a choice. Under natural assumptions on the decision-maker's strategy, forcing attention toward one item increases its likelihood of being chosen.

Indirect inference testing can be carried out with a variety of auxiliary models. Asymptotically these different models make no difference. However, the small sample properties can differ. We explore small sample power and estimation bias both with different variable combinations and descriptive...

Econometric analysis requires filtering techniques that are adapted to cater to data sequences that are short and that have strong trends. Whereas the economists have tended to conduct their analyses in the time domain, the engineers have emphasised the frequency domain. This paper places its...

This article has provided a critical review of sampling procedures in the context of Sierra Leone. The basics of the two major types of sampling procedures (probability and non-probability) have been explained, with a view of shedding light on their usage to assist researchers in their pursuance...

The estimation of the holding periods of financial products has to be done in a dynamic process in which the size of the observation time interval influences the result. Small intervals will produce smaller average holding periods than bigger ones. The approach developed in this paper offers the...

In India, 52-98 million people live in urban slums, and 59% of slums are "non-notified" or lack legal recognition by the government. In this paper, we use data on 2,901 slums from four waves of the National Sample Survey (NSS) spanning almost 20 years to test the hypothesis that non-notified...

This paper proposes new, simple, and more accurate statistical tests in a cointegrated system that allows for endogenous regressors and serially dependent errors. The approach involves first transforming the time series using orthonormal basis functions in L²[0,1], which has energy concentrated...

We propose a new method to implement the Business Time Sampling (BTS) scheme for high-frequency financial data. We compute a time-transformation (TT) function using the intraday integrated volatility estimated by a jump-robust method. The BTS transactions are obtained using the inverse of the TT...

The main objective of this work is to develop a detailed step-by-step guide to the development and application of a new class of efficient Monte Carlo methods to solve practically important problems faced by insurers under the new solvency regulations. In particular, a novel Monte Carlo method...

To promote digital transformation, equal emphasis needs to be placed on digital skills development as to infrastructure development. Integral to investment in digital skills development is the subsequent management and evaluation of digital training programmes. This paper assesses mechanisms to...

The estimation of the holding periods of financial products has to be done in a dynamic process in which the size of the observation time interval influences the result. Small intervals will produce smaller average holding periods than bigger ones. The approach developed in this paper offers the...

In a randomized control trial, the precision of an average treatment effect estimator and the power of the corresponding t-test can be improved either by collecting data on additional individuals, or by collecting additional covariates that predict the outcome variable. We propose the use of...

In a randomized control trial, the precision of an average treatment effect estimator and the power of the corresponding t-test can be improved either by collecting data on additional individuals, or by collecting additional covariates that predict the outcome variable. We propose the use of...