The environmental effect of technical change: A spatial model using city-level data in China

Abstract This article introduces a general equilibrium model of endogenous technical change through basic and applied research. Basic research differs from applied research in the nature and the magnitude of the generated spillovers. We propose a novel way of empirically identifying these spillovers and embed them in a framework with private firms and a public research sector. After characterizing the equilibrium, we estimate our model using micro-level data on research expenditures by French firms. Our key finding is that uniform research subsidies can accentuate the dynamic misallocation in the economy by oversubsidizing applied research. Policies geared towards public basic research and its interaction with the private sector are significantly welfare-improving.

Download Full-text

Unpacking Skill Bias: Automation and New Tasks

AEA Papers and Proceedings ◽

10.1257/pandp.20201063 ◽

2020 ◽

Vol 110 ◽

pp. 356-361

Author(s):

Daron Acemoglu ◽

Pascual Restrepo

Keyword(s):

Technical Change ◽

Canonical Model ◽

Skill Premium ◽

Real Wages ◽

Skill Bias ◽

The Past ◽

Level Data ◽

Unskilled Workers ◽

Productivity Gains ◽

Industry Level Data

We extend the canonical model of skill-biased technical change by modeling the allocation of tasks to factors and allowing for automation and the creation of new tasks. In our model, factor prices depend on the set of tasks they perform. Automation can reduce real wages and generate sizable changes in inequality associated with small productivity gains. New tasks can increase or reduce inequality depending on whether they are performed by skilled or unskilled workers. Industry-level data suggest that automation significantly contributed to the rising skill premium, while new tasks reduced inequality in the past but have contributed to inequality recently.

Download Full-text

New Evidence on the Construct Validity of the ASI-3 and the Dimensional Conceptualization of Trait Anxiety Sensitivity From IRT Modeling

European Journal of Psychological Assessment ◽

10.1027/1015-5759/a000284 ◽

2017 ◽

Vol 33 (3) ◽

pp. 181-189 ◽

Cited By ~ 2

Author(s):

Christoph J. Kemper ◽

Michael Hock

Keyword(s):

Construct Validity ◽

Anxiety Sensitivity ◽

Latent Class ◽

Dimensional Structure ◽

Sensitivity Index ◽

Response Scale ◽

Established Risk Factor ◽

Irt Models ◽

Level Data ◽

Extreme Response

Abstract. Anxiety Sensitivity (AS) denotes the tendency to fear anxiety-related sensations. Trait AS is an established risk factor for anxiety pathology. The Anxiety Sensitivity Index-3 (ASI-3) is a widely used measure of AS and its three most robust dimensions with well-established construct validity. At present, the dimensional conceptualization of AS, and thus, the construct validity of the ASI-3 is challenged. A latent class structure with two distinct and qualitatively different forms, an adaptive form (normative AS) and a maladaptive form (AS taxon, predisposing for anxiety pathology) was postulated. Item Response Theory (IRT) models were applied to item-level data of the ASI-3 in an attempt to replicate previous findings in a large nonclinical sample (N = 2,603) and to examine possible interpretations for the latent discontinuity observed. Two latent classes with a pattern of distinct responses to ASI-3 items were found. However, classes were indicative of participant’s differential use of the response scale (midpoint and extreme response style) rather than differing in AS content (adaptive and maladaptive AS forms). A dimensional structure of AS and the construct validity of the ASI-3 was supported.

Download Full-text

Personal Goals of Older Female Twins

European Psychologist ◽

10.1027/1016-9040.14.2.160 ◽

2009 ◽

Vol 14 (2) ◽

pp. 160-167 ◽

Cited By ~ 14

Author(s):

Katariina Salmela-Aro ◽

Sanna Read ◽

Jari-Erik Nurmi ◽

Markku Koskenvuo ◽

Jaakko Kaprio ◽

...

Keyword(s):

Physical Exercise ◽

Independent Living ◽

Environmental Effect ◽

Close Relationships ◽

Environmental Influence ◽

Genetic Effect ◽

Additive Genetic Effect ◽

Personal Goals ◽

Cultural Activities ◽

The Individual

This study examined genetic and environmental influences on older women’s personal goals by using data from the Finnish Twin Study on Aging. The interview for the personal goals was completed by 67 monozygotic (MZ) pairs and 75 dizygotic (DZ) pairs. The tetrachoric correlations for personal goals related to health and functioning, close relationships, and independent living were higher in MZ than DZ twins, indicating possible genetic influence. The pattern of tetrachoric correlations for personal goals related to cultural activities, care of others, and physical exercise indicated environmental influence. For goals concerning health and functioning, independent living, and close relationships, additive genetic effect accounted for about half of the individual variation. The rest was the result of a unique environmental effect. Goals concerning physical exercise and care of others showed moderate common environmental effect, while the rest of the variance was the result of a unique environmental effect. Personal goals concerning cultural activities showed unique environmental effects only.

Download Full-text

Modeling Intraindividual Variability in Three-Level Multilevel Models

Methodology ◽

10.1027/1614-2241/a000150 ◽

2018 ◽

Vol 14 (3) ◽

pp. 95-108 ◽

Cited By ~ 4

Author(s):

Steffen Nestler ◽

Katharina Geukes ◽

Mitja D. Back

Keyword(s):

Multilevel Model ◽

Multilevel Models ◽

Mixed Effects ◽

Repeated Measurements ◽

Scale Model ◽

Suggested Approach ◽

Psychological Study ◽

Level Data ◽

Ecological Momentary ◽

Momentary Assessment

Abstract. The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.

Download Full-text