scholarly journals Measuring the Impacts of Teachers: Comment

2017 ◽  
Vol 107 (6) ◽  
pp. 1656-1684 ◽  
Author(s):  
Jesse Rothstein
Keyword(s):  
North Carolina ◽  
Teacher Effectiveness ◽  
Value Added ◽  
Causal Effects ◽  
Student Preparedness ◽  
Long Run ◽  
Student Sorting ◽  
Moderate Bias ◽  
Quasi Experiment

Chetty, Friedman, and Rockoff (2014a, b) study value-added (VA) measures of teacher effectiveness. CFR (2014a) exploits teacher switching as a quasi-experiment, concluding that student sorting creates negligible bias in VA scores. CFR (2014b) finds VA scores are useful proxies for teachers' effects on students' long-run outcomes. I successfully reproduce each in North Carolina data. But I find that the quasi-experiment is invalid, as teacher switching is correlated with changes in student preparedness. Adjusting for this, I find moderate bias in VA scores, perhaps 10–35 percent as large, in variance terms, as teachers' causal effects. Long-run results are sensitive to controls and cannot support strong conclusions. (JEL H75, I21, J45)

Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique

2011 ◽  
Vol 6 (1) ◽  
pp. 18-42 ◽  
Author(s):  
Cory Koedel ◽  
Julian R. Betts
Keyword(s):  
Teacher Effectiveness ◽  
Value Added ◽  
Classroom Teaching ◽  
First Year ◽  
Value Added Models ◽  
Value Added Model ◽  
Extended Analysis ◽  
Research Questions ◽  
Value Added Modeling ◽  
Student Sorting

Value-added modeling continues to gain traction as a tool for measuring teacher performance. However, recent research questions the validity of the value-added approach by showing that it does not mitigate student-teacher sorting bias (its presumed primary benefit). Our study explores this critique in more detail. Although we find that estimated teacher effects from some value-added models are severely biased, we also show that a sufficiently complex value-added model that evaluates teachers over multiple years reduces the sorting bias problem to statistical insignificance. One implication of our findings is that data from the first year or two of classroom teaching for novice teachers may be insufficient to make reliable judgments about quality. Overall, our results suggest that in some cases value-added modeling will continue to provide useful information about the effectiveness of educational inputs.

scholarly journals Student Sorting and Bias in Value-Added Estimation: Selection on Observables and Unobservables

2009 ◽  
Vol 4 (4) ◽  
pp. 537-571 ◽  
Author(s):  
Jesse Rothstein
Keyword(s):  
Value Added ◽  
Fourth Grade ◽  
Causal Effects ◽  
Fifth Grade ◽  
Amount Of Information ◽  
Value Added Models ◽  
Sorting Process ◽  
Unobserved Variables ◽  
Student Sorting

Nonrandom assignment of students to teachers can bias value-added estimates of teachers' causal effects. Rothstein (2008, 2010) shows that typical value-added models indicate large counterfactual effects of fifth-grade teachers on students' fourth-grade learning, indicating that classroom assignments are far from random. This article quantifies the resulting biases in estimates of fifth-grade teachers' causal effects from several value-added models, under varying assumptions about the assignment process. If assignments are assumed to depend only on observables, the most commonly used specifications are subject to important bias, but other feasible specifications are nearly free of bias. I also consider the case in which assignments depend on unobserved variables. I use the across-classroom variance of observables to calibrate several models of the sorting process. Results indicate that even the best feasible value-added models may be substantially biased, with the magnitude of the bias depending on the amount of information available for use in classroom assignments.

What Do Surveys of Program Completers Tell Us About Teacher Preparation Quality?

2019 ◽  
Vol 72 (1) ◽  
pp. 11-26
Author(s):  
Kevin C. Bastian ◽  
Min Sun ◽  
Heather Lynn
Keyword(s):  
North Carolina ◽  
Teacher Preparation ◽  
Survey Data ◽  
Teacher Effectiveness ◽  
Outcome Measures ◽  
Value Added ◽  
Teacher Preparation Program ◽  
Opportunities To Learn ◽  
Program Accountability ◽  
K 12

Surveys of teacher preparation program (TPP) completers have become one widely used measure for program accountability and improvement, yet there is little evidence as to whether perceptions of preparation experiences predict the workforce outcomes of teachers. In the present study, we use statewide completer survey data from North Carolina to assess whether perceptions of preparation quality and opportunities to learn during teacher preparation predict completers’ value-added estimates, evaluation ratings, and retention. We perform multiple analyses to address validity concerns—that is, selection into TPPs, sorting into K-12 schools, simultaneity in survey and outcome measures, and differential survey response rates across TPPs. Results are not always consistent across these analyses; however, evidence suggests that completer perceptions are modestly associated with teacher effectiveness and retention. Continued research can further address validity concerns and build a body of evidence on completer perceptions and teacher outcomes.

scholarly journals Linking Teacher Quality, Student Attendance, and Student Achievement

2016 ◽  
Vol 11 (2) ◽  
pp. 125-149 ◽  
Author(s):  
Seth Gershenson
Keyword(s):  
North Carolina ◽  
Teacher Effectiveness ◽  
Behavioral Outcomes ◽  
Value Added ◽  
Student Attendance ◽  
A Value ◽  
Primary School Student ◽  
Teachers And Students ◽  
Potential Impact ◽  
Over Time

Research on the effectiveness of educational inputs, particularly research on teacher effectiveness, typically overlooks teachers’ potential impact on behavioral outcomes, such as student attendance. Using longitudinal data on teachers and students in North Carolina I estimate teacher effects on primary school student absences in a value-added framework. The analysis yields two main findings: First, teachers have arguably causal, statistically significant effects on student absences that persist over time. Second, teachers who improve test scores do not necessarily improve student attendance, suggesting that effective teaching is multidimensional and teachers who are effective in one domain are not necessarily effective in others.

Open Door System and Endogenous Growth in Indian Economy: An Empirical Analysis on the Role of Human Capital and R&D in Explaining Industrial Productivity

2021 ◽  
Vol 46 (1) ◽  
pp. 24-37
Author(s):  
Arjun K. ◽  
Sanjay Kumar ◽  
A. Sankaran ◽  
Mousumi Das
Keyword(s):  
Human Capital ◽  
Exchange Rate ◽  
Real Exchange Rate ◽  
Endogenous Growth ◽  
Value Added ◽  
Capital Formation ◽  
Knowledge Capital ◽  
Test Technique ◽  
Long Run ◽  
The Impact

The present study investigates the impact of human capital, knowledge capital which is a function of human capital, and real exchange rate scenario in explaining long-run industrial total factor productivity (TFP) from 1980 to 2015 on the theoretical basis of the open endogenous growth model. The variables employed in the contemporary study include manufacturing value added (MNVA) as industrial output measure, gross fixed capital formation (GFCF) as a measure of capital and labour input which is measured using employment data. Gross enrolment ratio (GER) is taken as a measure for human capital formation, expenditure on research and development (R&D) as a proxy for knowledge capital, and real exchange rate indicates global economic shocks. The study involves estimating TFP for Industrial Sector during the post-liberalization period by employing Cobb-Douglas production function. The ARDL bounds test technique for cointegration revealed long-run relation among the varying factors studied. The Toda-Yamamoto causality test concluded bi-directional causality running between, R&D expenditure and Industrial TFP which sends a strong signal to the policymakers for a well-framed long-term integrated approach for human & knowledge capital formation which will act as a strong impetus for manufacturing firms to come up in terms of augmenting production and productivity and expanding foreign market horizon. JEL Classification: D24, E2, J24

scholarly journals Dynamic Integrated Model for Assessing Fisheries: Discard Bans as an Implicit Value-Added Tax

2021 ◽  
Author(s):  
Jose Maria Da Rocha ◽  
Javier García-Cutrín ◽  
Maria-Jose Gutiérrez ◽  
Raul Prellezo ◽  
Eduardo Sanchez
Keyword(s):  
Value Added ◽  
Point Of View ◽  
Value Added Tax ◽  
Biological Variables ◽  
A Value ◽  
Long Run ◽  
The Social ◽  
Negative Effect ◽  
Short Run ◽  
The Impact

AbstractIntegrated economic models have become popular for assessing climate change. In this paper we show how these methods can be used to assess the impact of a discard ban in a fishery. We state that a discard ban can be understood as a confiscatory tax equivalent to a value-added tax. Under this framework, we show that a discard ban improves the sustainability of the fishery in the short run and increases economic welfare in the long run. In particular, we show that consumption, capital and wages show an initial decrease just after the implementation of the discard ban then recover after some periods to reach their steady-sate values, which are 16–20% higher than the initial values, depending on the valuation of the landed discards. The discard ban also improves biological variables, increasing landings by 14% and reducing discards by 29% on the initial figures. These patterns highlight the two channels through which discard bans affect a fishery: the tax channel, which shows that the confiscation of landed discards reduces the incentive to invest in the fishery; and the productivity channel, which increases the abundance of the stock. Thus, during the first few years after the implementation of a discard ban, the negative effect from the tax channel dominates the positive effect from the productivity channel, because the stock needs time to recover. Once stock abundance improves, the productivity channel dominates the tax channel and the economic variables rise above their initial levels. Our results also show that a landed discards valorisation policy is optimal from the social welfare point of view provided that incentives to increase discards are not created.

scholarly journals Energy Prices, Real Estate Sales and Industrial Output in China

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1847 ◽  
Author(s):  
K. Chau ◽  
Gaolu Zou
Keyword(s):  
Real Estate ◽  
Value Added ◽  
Industrial Sector ◽  
Data Series ◽  
Energy Prices ◽  
Industrial Output ◽  
Energy Efficient Buildings ◽  
Long Run ◽  
Different Types ◽  
Short Run

A majority of energy is consumed to control the indoor environment for human activities and industrial production. The demand for energies for these two uses are reflected in demand for different types of real estate and the volume of industrial outputs. The purpose of this study is to examine the long-run equilibrium and short-run dynamics between real energy prices and demand for different types of real estate and industrial output in China. Energy prices are measured in the real price of fuels and power. Demand for different types of real estate is measured in their sales volume in the first hand market, that is, floor areas of new real estate sold by developers. Industrial output is measured by the net output (value added) of the industrial sector. All data series were tested for stationarity (i.e., the existence of a unit root) before testing for a co-integration relationship. We found no long-term equilibrium relationship between energy prices and the demand for real estate and industrial output as predicted by theory, probably due to increased supply of energy efficient buildings. There is also no short-run relationship between energy prices and demand for housing due to the increase in vacancy rate resulting from speculative demand for housing. However, demand for commercial properties appeared to lead energy prices. Finally, there is strong evidence suggesting that an increase in energy prices will significantly reduce industrial output but not vice versa.

scholarly journals PELATIHAN EMOTIONAL INTELLIGENCE UNTUK MENINGKATKAN TEACHER EFFECTIVENESS PADA GURU SEKOLAH DASAR

2021 ◽  
Vol 6 (2) ◽  
pp. 245
Author(s):  
Cindy Adhianty Tupan ◽  
Setyani Alfinuha
Keyword(s):  
Emotional Intelligence ◽  
Teacher Effectiveness ◽  
Test Design ◽  
Post Test ◽  
Quasi Experiment

Peran guru sangat penting dalam mendukung performa akademik dan prestasi siswa. Pentingnya peran guru terkadang tidak diimbangi dengan keterampilan efektivitas guru dalam mengajar (teacher effectiveness). Pengukuran awal penelitian yang dilakukan menunjukkan hasil bahwa teacher effectiveness tergolong rendah. Padahal teacher effectiveness penting dimiliki guru untuk menunjang proses mengajar. Oleh karena itu peneliti berupaya memberikan pelatihan emotional intelligence untuk meningkatkan teacher effectiveness. Penelitian ini bertujuan untuk mengetahui efektivitas pelatihan emotional intelligence dalam meningkatkan teacher effectiveness pada guru. Partisipan penelitian ini berjumlah 21 guru di salah satu sekolah dasar di Surabaya. Penelitian ini merupakan sebuah quasi-experiment dengan menggunakan non-randomized one group pre-test post-test design. Pelatihan terdiri dari enam sesi yang dibagi dalam tiga pertemuan. Metode pengolahan data yang digunakan dalam penelitian ini adalah uji beda menggunakan aplikasi SPSS 16.0. Hasil intervensi menunjukkan bahwa terjadi peningkatan teacher effectivenesspada guru setelah diberikan pelatihan. Follow-up dilakukan dua minggu setelah pelatihan diberikan. Hasil follow-up menunjukkan bahwa tingkat teacher effectiveness cenderung tetap sehingga dapat disimpulkan bahwa efek pelatihan relatif bertahan pada partisipan penelitian.

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