Search results

1 – 10 of 808
Book part
Publication date: 13 May 2017

Jasjeet S. Sekhon and Rocío Titiunik

We discuss the two most popular frameworks for identification, estimation and inference in regression discontinuity (RD) designs: the continuity-based framework, where the…

Abstract

We discuss the two most popular frameworks for identification, estimation and inference in regression discontinuity (RD) designs: the continuity-based framework, where the conditional expectations of the potential outcomes are assumed to be continuous functions of the score at the cutoff, and the local randomization framework, where the treatment assignment is assumed to be as good as randomized in a neighborhood around the cutoff. Using various examples, we show that (i) assuming random assignment of the RD running variable in a neighborhood of the cutoff implies neither that the potential outcomes and the treatment are statistically independent, nor that the potential outcomes are unrelated to the running variable in this neighborhood; and (ii) assuming local independence between the potential outcomes and the treatment does not imply the exclusion restriction that the score affects the outcomes only through the treatment indicator. Our discussion highlights key distinctions between “locally randomized” RD designs and real experiments, including that statistical independence and random assignment are conceptually different in RD contexts, and that the RD treatment assignment rule places no restrictions on how the score and potential outcomes are related. Our findings imply that the methods for RD estimation, inference, and falsification used in practice will necessarily be different (both in formal properties and in interpretation) according to which of the two frameworks is invoked.

Details

Regression Discontinuity Designs
Type: Book
ISBN: 978-1-78714-390-6

Keywords

Content available
Book part
Publication date: 13 May 2017

Abstract

Details

Regression Discontinuity Designs
Type: Book
ISBN: 978-1-78714-390-6

Content available
Book part
Publication date: 13 May 2017

Abstract

Details

Regression Discontinuity Designs
Type: Book
ISBN: 978-1-78714-390-6

Book part
Publication date: 13 May 2017

Luke Keele, Scott Lorch, Molly Passarella, Dylan Small and Rocío Titiunik

We study research designs where a binary treatment changes discontinuously at the border between administrative units such as states, counties, or municipalities, creating a…

Abstract

We study research designs where a binary treatment changes discontinuously at the border between administrative units such as states, counties, or municipalities, creating a treated and a control area. This type of geographically discontinuous treatment assignment can be analyzed in a standard regression discontinuity (RD) framework if the exact geographic location of each unit in the dataset is known. Such data, however, is often unavailable due to privacy considerations or measurement limitations. In the absence of geo-referenced individual-level data, two scenarios can arise depending on what kind of geographic information is available. If researchers have information about each observation’s location within aggregate but small geographic units, a modified RD framework can be applied, where the running variable is treated as discrete instead of continuous. If researchers lack this type of information and instead only have access to the location of units within coarse aggregate geographic units that are too large to be considered in an RD framework, the available coarse geographic information can be used to create a band or buffer around the border, only including in the analysis observations that fall within this band. We characterize each scenario, and also discuss several methodological challenges that are common to all research designs based on geographically discontinuous treatment assignments. We illustrate these issues with an original geographic application that studies the effect of introducing copayments for the use of the Children’s Health Insurance Program in the United States, focusing on the border between Illinois and Wisconsin.

Details

Regression Discontinuity Designs
Type: Book
ISBN: 978-1-78714-390-6

Keywords

Article
Publication date: 14 January 2022

Gaowen Kong

The authors emphasize the information role of earnings management and how it may be used to “mislead some stakeholders about the underlying economic performance of the company or…

Abstract

Purpose

The authors emphasize the information role of earnings management and how it may be used to “mislead some stakeholders about the underlying economic performance of the company or to influence contractual outcomes that depend on reported accounting numbers.” Specifically, the authors examine the causal effect of tax incentives on private firms' earnings management based on a corporate tax reform in China.

Design/methodology/approach

In December 2001, China implemented a tax collection reform which moved the collection of corporate income taxes from the local tax bureau to the state tax bureau. This reform results in exogenous variations in the effective tax rate among similar firms established before and after 2002. The authors apply a regression discontinuity design and use the generated variation in the effective tax rate to investigate the impact of taxes on firm earnings management.

Findings

The authors find that tax reduction substantially increases private firms' incentives to manage earnings information, and such effect is particularly pronounced when tax collection intensity and government interventions are low. Further evidence shows that lower tax rates stimulate firms' investment, inventory turnover and recruitment of skilled human capital. A plausible mechanism is that private firms signal a promising outlook by managing earnings to attain greater financing and improve investment/operation levels when financial constraints are removed.

Originality/value

First, the authors present the causal effects of tax incentives on private firm's earnings management, which deepens the authors’ understanding on the determinants of firm's earnings information production. Second, this study also contributes to the literature on tax-induced earnings management. Third, the authors believe that this topic offers clear policy implications and would be of particular interest to regulators.

Details

China Finance Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1398

Keywords

Book part
Publication date: 7 December 2023

Heeyun Kim and Paula Clasing-Manquian

Education researchers have been urged to utilize causal inference methods to estimate the policy effect more rigorously. While randomized controlled trials (RCTs) are the gold…

Abstract

Education researchers have been urged to utilize causal inference methods to estimate the policy effect more rigorously. While randomized controlled trials (RCTs) are the gold standard for assessing causality, RCTs are infeasible in some educational settings, particularly when ethical concerns or high cost are involved. Quasi-experimental research designs are the best alternative approach to study educational topics not amenable to RCTs, as they mimic experimental conditions and use statistical techniques to reduce bias from variables omitted in the empirical models. In this chapter, we introduce and discuss the core concepts, applicability, and limitations of three quasi-experimental methods in higher education research (i.e., difference-in-differences, instrumental variables, and regression discontinuity). By introducing each of these techniques, we aim to expand the higher education researcher's toolbox and encourage the use of these quasi-experimental methods to evaluate educational interventions.

Article
Publication date: 16 December 2019

A. Hussain Lal, Vishnu K.R., A. Noorul Haq and Jeyapaul R.

The purpose of this paper is to minimize the mean flow time in open shop scheduling problem (OSSP). The scheduling problems consist of n jobs and m machines, in which each job has…

Abstract

Purpose

The purpose of this paper is to minimize the mean flow time in open shop scheduling problem (OSSP). The scheduling problems consist of n jobs and m machines, in which each job has O operations. The processing time for 50 OSSP was generated using a linear congruential random number.

Design/methodology/approach

Different evolutionary algorithms are used to minimize the mean flow time of OSSP. This research study used simulated annealing (SA), Discrete Firefly Algorithm and a Hybrid Firefly Algorithm with SA. These methods are referred as A1, A2 and A3, respectively.

Findings

A comparison of the results obtained from the three methods shows that the Hybrid Firefly Algorithm with SA (A3) gives the best mean flow time for 76 percent instances. Also, it has been observed that as the number of jobs increases, the chances of getting better results also increased. Among the first 25 problems (i.e. job ranging from 3 to 7), A3 gave the best results for 13 instances, i.e., for 52 percent of the first 25 instances. While for the last 25 problems (i.e. Job ranging from 8 to 12), A3 gave the best results for all 25 instances, i.e. for 100 percent of the problems.

Originality/value

From the literature it has been observed that no researchers have attempted to solve OOSPs using Firefly Algorithm (FA). In this research work an attempt has been made to apply the FA and its hybridization to solve OSSP. Also the research work carried out in this paper can also be applied for a real-time Industrial problem.

Details

Journal of Advances in Management Research, vol. 17 no. 2
Type: Research Article
ISSN: 0972-7981

Keywords

Article
Publication date: 5 September 2016

Ying (Jessica) Cao, Calum Turvey, Jiujie Ma, Rong Kong, Guangwen He and Jubo Yan

The purpose of this paper is to investigate whether negative incentives in the pay-for-performance mechanism would trigger loan officers to strategically reject potentially good…

Abstract

Purpose

The purpose of this paper is to investigate whether negative incentives in the pay-for-performance mechanism would trigger loan officers to strategically reject potentially good loans. If so, what is the feasible solution to alleviate the problem.

Design/methodology/approach

A framed field experiment was conducted to test loan decision behaviors using loan officers from Rural Credit Cooperatives in Shandong, China. A 2 by 2 between-subject design was adopted to generate variation in incentives and prior information about credit risks.

Findings

Results showed that loan officers did ration credit by rejecting more loans when facing risks of personal income loss. However, providing risk information about the application pool boosted the approval rate and offset the behavioral responses by a roughly same magnitude.

Research limitations/implications

Findings in this study suggest that certain institutional settings can result in credit rationing via strategic loan misclassification. Further, information sometimes generates similar effects as those costly incentives or mechanisms that are not implementable in practice.

Originality/value

This study adopted an innovative monetized experimental design that allows researchers to examine the (otherwise unobservable) trade-offs between Type I and Type II error in loan misclassification as incentives change. In addition, an anchoring prior information treatment is used to solicit the relative power of almost costless information and costly monetary incentives, and to point out a potentially feasible solution.

Details

Agricultural Finance Review, vol. 76 no. 3
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 8 June 2022

Noppanon Homsud and Nopadol Rompho

This study aims to determine the effect of cognitive biases, that is, anchoring effect, illusion of control, and endowment effect, on customer satisfaction.

Abstract

Purpose

This study aims to determine the effect of cognitive biases, that is, anchoring effect, illusion of control, and endowment effect, on customer satisfaction.

Design/methodology/approach

An experimental design was applied using 524 undergraduate students as participants. A three-way ANOVA was employed for data analysis.

Findings

Positive relationships were found between cognitive biases and customer satisfaction. However, no such relationships were found between the interactions of various types of cognitive bias and customer satisfaction, except the interaction between illusion of control and endowment effect.

Research limitations/implications

This study focuses only on three types of cognitive biases; thus, it cannot be generalized to other such systematic patterns.

Practical implications

Marketers can introduce cognitive bias when implementing marketing campaigns to boost customer satisfaction.

Originality/value

This study expands the knowledge boundary by addressing the impact of the interaction between various aspects of cognitive bias that drive customer satisfaction.

Details

Asia-Pacific Journal of Business Administration, vol. 15 no. 5
Type: Research Article
ISSN: 1757-4323

Keywords

Article
Publication date: 25 December 2023

Zihan Dang and Naiming Xie

Assembly line is a common production form and has been effectively used in many industries, but the imprecise processing time of each process makes production line balancing and…

Abstract

Purpose

Assembly line is a common production form and has been effectively used in many industries, but the imprecise processing time of each process makes production line balancing and capacity forecasting the most troublesome problems for production managers. In this paper, uncertain man-hours are represented as interval grey numbers, and the optimization problem of production line balance in the case of interval grey man-hours is studied to better evaluate the production line capacity.

Design/methodology/approach

First, this paper constructs the basic model of assembly line balance optimization for the single-product scenario, and on this basis constructs an assembly line balance optimization model under the multi-product scenario with the objective function of maximizing the weighted greyscale production line balance rate, second, this paper designs a simulated annealing algorithm to solve problem. A neighborhood search strategy is proposed, based on assembly line balance optimization, an assembly line capacity evaluation method with interval grey man-hour characteristics is designed.

Findings

This paper provides a production line balance optimization scheme with uncertain processing time for multi-product scenarios and designs a capacity evaluation method to provide managers with scientific management strategies so that decision-makers can scientifically solve the problems that the company's design production line is quite different from the actual production situation.

Originality/value

There are few literary studies on combining interval grey number with assembly line balance optimization. Therefore, this paper makes an important contribution in this regard.

Details

Grey Systems: Theory and Application, vol. 14 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

1 – 10 of 808