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Journal articles on the topic 'Marginal effects'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

Caprara, Gian Vittorio, Kenneth A. Dodge, Concetta Pastorelli, and Arnaldo Zelli. "The Effects of Marginal Deviations on Behavioral Development." European Psychologist 11, no. 2 (2006): 79–89. http://dx.doi.org/10.1027/1016-9040.11.2.79.

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This investigation was conceptually framed within the theory of marginal deviations ( Caprara & Zimbardo, 1996 ) and sought evidence for the general hypothesis that some children who initially show marginal behavioral problems may, over time, develop more serious problems depending partly on other personal and behavioral characteristics. To this end, the findings of two studies conducted, respectively, with American elementary school children and Italian middle school students are reviewed. These two studies show that hyperactivity, cognitive difficulties, low social preference, and lack o

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2

Bartus, Tamás. "Estimation of Marginal Effects using Margeff." Stata Journal: Promoting communications on statistics and Stata 5, no. 3 (2005): 309–29. http://dx.doi.org/10.1177/1536867x0500500303.

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This article describes the user-written program margeff, which enables the fast estimation of (average) marginal effects. Besides describing the program, this article offers a new discussion of some problems that are related to computation of marginal effects. I will argue that (1) marginal effects computed at means are not good approximations of average marginal effects, computed as means of marginal effects evaluated at each observations, if some of the parameter estimates are large; (2) both average marginal effects and marginal effects computed at means might produce wrong estimates for du

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3

López-Feldman, Alejandro. "Decomposing Inequality and Obtaining Marginal Effects." Stata Journal: Promoting communications on statistics and Stata 6, no. 1 (2006): 106–11. http://dx.doi.org/10.1177/1536867x0600600107.

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4

Pepinsky, Thomas B. "Visual heuristics for marginal effects plots." Research & Politics 5, no. 1 (2018): 205316801875666. http://dx.doi.org/10.1177/2053168018756668.

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Common visual heuristics used to interpret marginal effects plots are susceptible to Type-1 error. This susceptibility varies as a function of (a) sample size, (b) stochastic error in the true data generating process, and (c) the relative size of the main effects of the causal variable versus the moderator. I discuss simple alternatives to these standard visual heuristics that may improve inference and do not depend on regression parameters.

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5

Mullahy, John. "Marginal effects in multivariate probit models." Empirical Economics 52, no. 2 (2016): 447–61. http://dx.doi.org/10.1007/s00181-016-1090-8.

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6

MOFFITT. "Estimating Marginal Treatment Effects in Heterogeneous Populations." Annales d'Économie et de Statistique, no. 91/92 (2008): 239. http://dx.doi.org/10.2307/27917247.

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7

Anderson, Soren, and Richard G. Newell. "Simplified marginal effects in discrete choice models." Economics Letters 81, no. 3 (2003): 321–26. http://dx.doi.org/10.1016/s0165-1765(03)00212-x.

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8

Greene, William. "Marginal effects in the censored regression model." Economics Letters 64, no. 1 (1999): 43–49. http://dx.doi.org/10.1016/s0165-1765(99)00059-2.

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9

Saha, Atanu, Oral Capps, and Patrick J. Byrne. "Calculating marginal effects in dichotomous - continuous models." Applied Economics Letters 4, no. 3 (1997): 181–85. http://dx.doi.org/10.1080/135048597355474.

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10

Smith, C. L. "UGC cuts and medical services: marginal effects." BMJ 292, no. 6526 (1986): 1017. http://dx.doi.org/10.1136/bmj.292.6526.1017-b.

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11

Mitani, Nobuhiro, and Susumu Kurihara. "Marginal Fermi-liquid theory and renormalization effects." Physica C: Superconductivity 192, no. 1-2 (1992): 230–36. http://dx.doi.org/10.1016/0921-4534(92)90765-5.

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12

Ren, Bijie. "The regional effects of marginal wage subsidies." Frontiers of Economics in China 3, no. 4 (2008): 598–626. http://dx.doi.org/10.1007/s11459-008-0030-8.

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13

Bland, James R., and Amanda C. Cook. "Random effects probit and logit: understanding predictions and marginal effects." Applied Economics Letters 26, no. 2 (2018): 116–23. http://dx.doi.org/10.1080/13504851.2018.1441498.

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14

Carvalho, Fernando Geraldo de, Nelson Silva Pinto, José Max Barbosa de Oliveira Júnior, and Leandro Juen. "Effects of marginal vegetation removal on Odonata communities." Acta Limnologica Brasiliensia 25, no. 1 (2013): 10–18. http://dx.doi.org/10.1590/s2179-975x2013005000013.

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AIM: Here we assess the effects of habitat degradation on individuals of the two suborders of Odonata community of Borecaia river sub-basin. More specifically, we tested the hypothesis that Anisoptera richness would be positively affected by removal of vegetation; on the other hand, Zygoptera richness would be adversely affected by virtue of their ecophysiological requirements; METHODS: We selected 10 streams of similar orders, six preserved and four degraded. Streams characterized as preserved had values of Index of Habitat Integrity (HII) above 0.70 (0.77 ± 0.07, mean ± SD) and continuous fo

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15

Neugebauer, Romain, and Mark van der Laan. "Nonparametric causal effects based on marginal structural models." Journal of Statistical Planning and Inference 137, no. 2 (2007): 419–34. http://dx.doi.org/10.1016/j.jspi.2005.12.008.

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16

Willett, W. C., and A. Ascherio. "Trans fatty acids: are the effects only marginal?" American Journal of Public Health 84, no. 5 (1994): 722–24. http://dx.doi.org/10.2105/ajph.84.5.722.

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17

Torres, Michelle. "Estimating controlled direct effects through marginal structural models." Political Science Research and Methods 8, no. 3 (2020): 391–408. http://dx.doi.org/10.1017/psrm.2020.3.

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AbstractWhen working with panel data, many researchers wish to estimate the direct effects of time-varying factors on future outcomes. However, when a baseline treatment affects both the confounders of further stages of the treatment and the outcome, the estimation of controlled direct effects (CDEs) using traditional regression methods faces a bias trade-off between confounding bias and post-treatment control. Drawing on research from the field of epidemiology, in this article I present a marginal structural modeling (MSM) approach that allows scholars to generate unbiased estimates of CDEs.

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18

Andresen, Martin Eckhoff. "Exploring Marginal Treatment Effects: Flexible Estimation Using Stata." Stata Journal: Promoting communications on statistics and Stata 18, no. 1 (2018): 118–58. http://dx.doi.org/10.1177/1536867x1801800108.

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In settings that exhibit selection on both levels and gains, marginal treatment effects (MTE) allow us to go beyond local average treatment effects and estimate the whole distribution of effects. In this article, I survey the theory behind MTE and introduce the package mtefe, which uses several estimation methods to fit MTE models. This package provides important improvements and flexibility over existing packages such as margte (Brave and Walstrum, 2014, Stata Journal 14: 191–217) and calculates various treatment-effect parameters based on the results. I illustrate the use of the package with

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19

Wang, Huixia Judy, Ian W. McKeague, and Min Qian. "Testing for marginal linear effects in quantile regression." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 80, no. 2 (2017): 433–52. http://dx.doi.org/10.1111/rssb.12258.

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20

Zhou, Xiang, and Yu Xie. "Marginal Treatment Effects from a Propensity Score Perspective." Journal of Political Economy 127, no. 6 (2019): 3070–84. http://dx.doi.org/10.1086/702172.

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21

Caudill, Steven B., and John D. Jackson. "Measuring Marginal Effects in Limited Dependent Variable Models." Statistician 38, no. 3 (1989): 203. http://dx.doi.org/10.2307/2348876.

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22

Careta, A., and F. Sagués. "Multiplicative noise effects on relaxations from marginal states." Physical Review A 44, no. 4 (1991): 2284–91. http://dx.doi.org/10.1103/physreva.44.2284.

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23

Royston, Patrick. "Marginscontplot: Plotting the Marginal Effects of Continuous Predictors." Stata Journal: Promoting communications on statistics and Stata 13, no. 3 (2013): 510–27. http://dx.doi.org/10.1177/1536867x1301300305.

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24

Abrevaya, Jason. "COMPUTING MARGINAL EFFECTS IN THE BOX–COX MODEL." Econometric Reviews 21, no. 3 (2002): 383–93. http://dx.doi.org/10.1081/etc-120015789.

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25

Stoker, Thomas M. "Smoothing bias in the measurement of marginal effects." Journal of Econometrics 72, no. 1-2 (1996): 49–84. http://dx.doi.org/10.1016/0304-4076(94)01715-8.

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26

Hasebe, Takuya. "Marginal effects of a bivariate binary choice model." Economics Letters 121, no. 2 (2013): 298–301. http://dx.doi.org/10.1016/j.econlet.2013.08.028.

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27

Bishop, A. R., A. Bussmann-Holder, O. V. Dolgov, et al. "Real and Marginal Isotope Effects in Cuprate Superconductors." Journal of Superconductivity and Novel Magnetism 20, no. 5 (2007): 393–96. http://dx.doi.org/10.1007/s10948-007-0235-6.

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28

Edlefsen, Lee E. "Income effects and the marginal utility of income." Economics Letters 17, no. 1-2 (1985): 5–9. http://dx.doi.org/10.1016/0165-1765(85)90116-8.

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29

Müller, Christopher. "Welfare Effects of Water Pricing in Germany." Water Economics and Policy 01, no. 04 (2015): 1550019. http://dx.doi.org/10.1142/s2382624x15500198.

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The observed two-part tariff price structure (consisting of a lump-sum price and linear marginal price) for drinking water in Germany does not reflect the cost structure reported in the literature. Recovering marginal costs from a sample of 251 German counties, we see that there are positive price-cost margins, while lump-sum prices are too low. A price structure readjustment along welfare economic principles (marginal cost pricing, lump-sum price ensures cost-recovery) would increase the mean consumer surplus by 0.037% of the local GDP or €[Formula: see text]2.129 million per county, assuming

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30

Bester, C. Alan, and Christian Hansen. "Identification of Marginal Effects in a Nonparametric Correlated Random Effects Model." Journal of Business & Economic Statistics 27, no. 2 (2009): 235–50. http://dx.doi.org/10.1198/jbes.2009.0017.

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31

Ma, Shujie, Jeffrey S. Racine, and Aman Ullah. "Nonparametric estimation of marginal effects in regression-spline random effects models." Econometric Reviews 39, no. 8 (2020): 792–825. http://dx.doi.org/10.1080/07474938.2020.1772569.

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32

Martin, Robert S. "Estimation of average marginal effects in multiplicative unobserved effects panel models." Economics Letters 160 (November 2017): 16–19. http://dx.doi.org/10.1016/j.econlet.2017.08.020.

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33

Fowler, Anthony. "Regular Voters, Marginal Voters and the Electoral Effects of Turnout." Political Science Research and Methods 3, no. 2 (2015): 205–19. http://dx.doi.org/10.1017/psrm.2015.18.

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How do marginal voters differ from regular voters? This article develops a method for comparing the partisan preferences of regular voters to those marginal voters whose turnout decisions are influenced by exogenous factors and applies it to two sources of variation in turnout in the United States—weather and election timing. In both cases, marginal voters are over 20 percentage points more supportive of the Democratic Party than regular voters—a significant divide. The findings suggest that the expansion or contraction of the electorate can have important consequences. Moreover, the findings

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34

Rios-Avila, Fernando. "Estimation of marginal effects for models with alternative variable transformations." Stata Journal: Promoting communications on statistics and Stata 21, no. 1 (2021): 81–96. http://dx.doi.org/10.1177/1536867x211000005.

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margins is a powerful postestimation command that allows the estimation of marginal effects for official and community-contributed commands, with well-defined predicted outcomes (see predict). While the use of factor-variable notation allows one to easily estimate marginal effects when interactions and polynomials are used, estimation of marginal effects when other types of transformations such as splines, logs, or fractional polynomials are used remains a challenge. In this article, I describe how margins‘s capabilities can be extended to analyze other variable transformations using the comma

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35

Lee, Ki-Hong, In-Sung Yeo, Benjamin M. Wu, et al. "Effects of Computer-Aided Manufacturing Technology on Precision of Clinical Metal-Free Restorations." BioMed Research International 2015 (2015): 1–5. http://dx.doi.org/10.1155/2015/619027.

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Purpose. The purpose of this study was to investigate the marginal fit of metal-free crowns made by three different computer-aided design/computer-aided manufacturing (CAD/CAM) systems.Materials and Methods. The maxillary left first premolar of a dentiform was prepared for all-ceramic crown restoration. Thirty all-ceramic premolar crowns were made, ten each manufactured by the Lava system, Cercon, and Cerec. Ten metal ceramic gold (MCG) crowns served as control. The marginal gap of each sample was measured under a stereoscopic microscope at 75x magnification after cementation. One-way ANOVA an

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36

Mabon, G. "Adaptive estimation of marginal random-effects densities in linear mixed-effects models." Mathematical Methods of Statistics 24, no. 2 (2015): 81–109. http://dx.doi.org/10.3103/s1066530715020015.

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37

Kaseeram, Irrshad, and Darma Mahadea. "Marginal Employment Growth Effects In The South African Economy." International Business & Economics Research Journal (IBER) 16, no. 2 (2017): 143–56. http://dx.doi.org/10.19030/iber.v16i2.9930.

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South Africa relative to its peers (upper middle income countries) suffers from high unemployment and sub-optimal economic growth. This study investigates the ‘marginal effects of employment’ with respect to real output and capital in South Africa, using annual data covering the period 1946-2015. It estimates the responsiveness of employment to real output growth and capital, employing the short and long-run dynamic interactions between these variables via the application of the VAR/VECM Johansen (1991) framework. The results show that there exists a statistically significant long-run co-integ

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38

Hoderlein, Stefan, and Enno Mammen. "Identification of Marginal Effects in Nonseparable Models Without Monotonicity." Econometrica 75, no. 5 (2007): 1513–18. http://dx.doi.org/10.1111/j.1468-0262.2007.00801.x.

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39

Bukhari, Csilla, Luminița Lazăr, Adriana Maria Monea, et al. "Effects of Viral and Bacterial Infections on Marginal Periodontium." Journal of Interdisciplinary Medicine 2, no. 2 (2017): 122–26. http://dx.doi.org/10.1515/jim-2017-0048.

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Abstract Background: There are several risk factors, general and local, which favor the onset of periodontal destruction, and their knowledge is essential to their correct identification and for the adoption of a suitable therapeutic management. The aim of the study was to assess periodontal health status of patients suffering from viral and bacterial infections and to determine the eventual relationship between periodontal diseases and infectious diseases. Material and methods: Twenty-five patients with a mean age of 25 years (range 23–27 years) admitted to the Clinic of Infectious Diseases o

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40

Ganter, William A. "Increasing importance of effects of marginal parts on reliability." Quality and Reliability Engineering International 6, no. 4 (1990): 285–88. http://dx.doi.org/10.1002/qre.4680060411.

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41

DAVIS, JAMES N. "Facilitating Effects of Marginal Glosses on Foreign Language Reading." Modern Language Journal 73, no. 1 (1989): 41–48. http://dx.doi.org/10.1111/j.1540-4781.1989.tb05308.x.

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42

Li, Lin, Hualei Zhai, Lixin Xie, Jun Cheng, and Weiwei Liu. "Therapeutic Effects of Lamellar Keratoplasty on Terrien Marginal Degeneration." Cornea 37, no. 3 (2018): 318–25. http://dx.doi.org/10.1097/ico.0000000000001325.

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43

Brave, Scott, and Thomas Walstrum. "Estimating Marginal Treatment Effects using Parametric and Semiparametric Methods." Stata Journal: Promoting communications on statistics and Stata 14, no. 1 (2014): 191–217. http://dx.doi.org/10.1177/1536867x1401400113.

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44

Kumbhakar, Subal C., and Kai Sun. "Derivation of marginal effects of determinants of technical inefficiency." Economics Letters 120, no. 2 (2013): 249–53. http://dx.doi.org/10.1016/j.econlet.2013.04.041.

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45

Carlevaro, Fabrizio, and Marc-Alexandre Sénégas. "Simplified marginal effects in discrete choice models: A correction." Economics Letters 92, no. 1 (2006): 44–46. http://dx.doi.org/10.1016/j.econlet.2006.01.012.

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46

Kwan-Hee Cho. "‘Marginal Man’ and ‘Marginal Literati’ ― Their Effects upon the Development of Early Novel in Korea and China." Journal of the research of chinese novels ll, no. 46 (2015): 211–30. http://dx.doi.org/10.17004/jrcn.2015..46.009.

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47

Mahrt, L., and Robert Heald. "Common Marginal Cold Pools." Journal of Applied Meteorology and Climatology 54, no. 2 (2015): 339–51. http://dx.doi.org/10.1175/jamc-d-14-0204.1.

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AbstractThis study examines marginal cold pools forming in a shallow valley. “Marginal” refers to cold pools that are generally weak and intermittent. Nineteen stations were instrumented with sonic anemometers and accurate slow-response temperature measurements. The vertical structure of the cold pool is determined from a 20-m tower on the valley floor that includes eight levels of sonic anemometers and eight additional levels of slow-response temperature. On the basis of the data analysis, the traditional concept of a cold pool must be generalized to include cold-pool intermittency, complex v

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48

Tsonaka, Roula, Diane van der Woude, and Jeanine Houwing-Duistermaat. "Marginal genetic effects estimation in family and twin studies using random-effects models." Biometrics 71, no. 4 (2015): 1130–38. http://dx.doi.org/10.1111/biom.12350.

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49

Fernández-Val, Iván. "Fixed effects estimation of structural parameters and marginal effects in panel probit models." Journal of Econometrics 150, no. 1 (2009): 71–85. http://dx.doi.org/10.1016/j.jeconom.2009.02.007.

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50

Versloot, P. M., J. P. Schröder-Van Der Elst, D. Van Der Heide, and L. Boogerd. "Effects of marginal iodine deficiency during pregnancy: iodide uptake by the maternal and fetal thyroid." American Journal of Physiology-Endocrinology and Metabolism 273, no. 6 (1997): E1121—E1126. http://dx.doi.org/10.1152/ajpendo.1997.273.6.e1121.

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Iodide uptake by the thyroid is an active process. Iodine deficiency and pregnancy are known to influence thyroid hormone metabolism. The aim of this study was to clarify the effects of iodine deficiency and pregnancy on iodide uptake by the thyroid. Radioiodide was injected intravenously into nonpregnant and 19-day pregnant rats receiving a normal or marginally iodine-deficient diet. The uptake of radioiodide by the thyroid was measured continuously for 4 h. The absolute iodide uptake by the maternal and fetal thyroid glands at 24 h was calculated by means of the urinary specific activity. Pr

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