Relevant bibliographies by topics / Fixed effect model

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fixed effect model'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 January 2023

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Journal articles on the topic "Fixed effect model"

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Spineli, Loukia M., and Nikolaos Pandis. "Meta-analysis: Fixed-effect model." American Journal of Orthodontics and Dentofacial Orthopedics 157, no. 1 (January 2020): 134–37. http://dx.doi.org/10.1016/j.ajodo.2019.10.008.

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Wang, Qunyong. "Fixed-Effect Panel Threshold Model using Stata." Stata Journal: Promoting communications on statistics and Stata 15, no. 1 (April 2015): 121–34. http://dx.doi.org/10.1177/1536867x1501500108.

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Wang, Hung-Jen, and Chia-Wen Ho. "Estimating fixed-effect panel stochastic frontier models by model transformation." Journal of Econometrics 157, no. 2 (August 2010): 286–96. http://dx.doi.org/10.1016/j.jeconom.2009.12.006.

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Spineli, Loukia M., and Nikolaos Pandis. "Fixed-effect versus random-effects model in meta-regression analysis." American Journal of Orthodontics and Dentofacial Orthopedics 158, no. 5 (November 2020): 770–72. http://dx.doi.org/10.1016/j.ajodo.2020.07.016.

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Jochmans, Koen, and Martin Weidner. "Fixed‐Effect Regressions on Network Data." Econometrica 87, no. 5 (2019): 1543–60. http://dx.doi.org/10.3982/ecta14605.

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This paper considers inference on fixed effects in a linear regression model estimated from network data. An important special case of our setup is the two‐way regression model. This is a workhorse technique in the analysis of matched data sets, such as employer–employee or student–teacher panel data. We formalize how the structure of the network affects the accuracy with which the fixed effects can be estimated. This allows us to derive sufficient conditions on the network for consistent estimation and asymptotically valid inference to be possible. Estimation of moments is also considered. We allow for general networks and our setup covers both the dense and the sparse case. We provide numerical results for the estimation of teacher value‐added models and regressions with occupational dummies.
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Xin, Yang, Xu Weidong, Xiang Lei, Zhu Wannian, and Tian Jiyao. "A Camouflage Effect Detection Model for Fixed Targets." Journal of Physics: Conference Series 1187, no. 4 (April 2019): 042097. http://dx.doi.org/10.1088/1742-6596/1187/4/042097.

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Gronau, Quentin F., Daniel W. Heck, Sophie W. Berkhout, Julia M. Haaf, and Eric-Jan Wagenmakers. "A Primer on Bayesian Model-Averaged Meta-Analysis." Advances in Methods and Practices in Psychological Science 4, no. 3 (July 2021): 251524592110312. http://dx.doi.org/10.1177/25152459211031256.

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Meta-analysis is the predominant approach for quantitatively synthesizing a set of studies. If the studies themselves are of high quality, meta-analysis can provide valuable insights into the current scientific state of knowledge about a particular phenomenon. In psychological science, the most common approach is to conduct frequentist meta-analysis. In this primer, we discuss an alternative method, Bayesian model-averaged meta-analysis. This procedure combines the results of four Bayesian meta-analysis models: (a) fixed-effect null hypothesis, (b) fixed-effect alternative hypothesis, (c) random-effects null hypothesis, and (d) random-effects alternative hypothesis. These models are combined according to their plausibilities given the observed data to address the two key questions “Is the overall effect nonzero?” and “Is there between-study variability in effect size?” Bayesian model-averaged meta-analysis therefore avoids the need to select either a fixed-effect or random-effects model and instead takes into account model uncertainty in a principled manner.
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Reich, Robin M., and Loukas G. Arvanitis. "Correcting for nonrandom errors in a fixed-effect model." Canadian Journal of Forest Research 19, no. 12 (December 1, 1989): 1550–54. http://dx.doi.org/10.1139/x89-236.

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In this article, a statistical method of estimating the microsite component (a nonrandom error) in a fixed-effect model is presented and discussed. The approach uses generalized least squares to partition the model variance into two components: one part due to microsite and the other one due to random errors. An iterative procedure is then used to solve for the maximum likelihood estimate of the microsite component. Application of the technique to a slash pine (Pinuselliottii Engelm. var. elliottii) spacing trial indicates that 30% of the variability in total tree height at age 6 years was due to microsite, whereas the remaining 70% was due to random errors.
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Lee, Seung-Chun. "A Bayesian inference for fixed effect panel probit model." Communications for Statistical Applications and Methods 23, no. 2 (March 31, 2016): 179–87. http://dx.doi.org/10.5351/csam.2016.23.2.179.

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LeBeau, Brandon, Yoon Ah Song, and Wei Cheng Liu. "Model Misspecification and Assumption Violations With the Linear Mixed Model: A Meta-Analysis." SAGE Open 8, no. 4 (October 2018): 215824401882038. http://dx.doi.org/10.1177/2158244018820380.

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This meta-analysis attempts to synthesize the Monte Carlo (MC) literature for the linear mixed model under a longitudinal framework. The meta-analysis aims to inform researchers about conditions that are important to consider when evaluating model assumptions and adequacy. In addition, the meta-analysis may be helpful to those wishing to design future MC simulations in identifying simulation conditions. The current meta-analysis will use the empirical type I error rate as the effect size and MC simulation conditions will be coded to serve as moderator variables. The type I error rate for the fixed and random effects will be explored as the primary dependent variable. Effect sizes were coded from 13 studies, resulting in a total of 4,002 and 621 effect sizes for fixed and random effects respectively. Meta-regression and proportional odds models were used to explore variation in the empirical type I error rate effect sizes. Implications for applied researchers and researchers planning new MC studies will be explored.
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Dissertations / Theses on the topic "Fixed effect model"

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Hansen, Elizabeth Ann. "Penalized likelihood estimation of a fixed-effect and a mixed-effect transfer function model." Diss., University of Iowa, 2006. http://ir.uiowa.edu/etd/58.

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Náglová, Zdeňka. "Podpory potravinářského sektoru ČR v kontextu s fondy EU a jejich dopady." Doctoral thesis, Česká zemědělská univerzita v Praze, 2016. http://www.nusl.cz/ntk/nusl-259705.

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Dissertation deals with the food industry. First, the economy of the sector in the branch structure and size of businesses is evaluated. The main attention is paid to the drawing subsidies by the food industry in the context of EU funds. The main objective of this thesis is to evaluate the effect of the subsidies on the economy of the food business. For the analysis fixed effect model was used. According to the results, there are significant differences in the impact of subsidies on the individual branches of the food industry. In most fields was demonstrated their ineffective use to increase business performance.
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Rasch, Dieter, Thomas Rusch, Marie Simeckova, Klaus D. Kubinger, Karl Moder, and Petr Simecek. "Tests of additivity in mixed and fixed effect two-way ANOVA models with single sub-class numbers." Springer, 2009. http://dx.doi.org/10.1070/s00362-009-0254-4.

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In variety testing as well as in psychological assessment, the situation occurs that in a two-way ANOVA-type model with only one replication per cell, analysis is done under the assumption of no interaction between the two factors. Tests for this situation are known only for fixed factors and normally distributed outcomes. In the following we will present five additivity tests and apply them to fixed and mixed models and to quantitative as well as to Bernoulli distributed data. We consider their performance via simulation studies with respect to the type-I-risk and power. Furthermore, two new approaches will be presented, one being a modification of Tukey's test and the other being a new experimental design to test for interactions.
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Frey, Reik. "International and domestic Migration Patterns : International immigration effect on internal out-migration patterns in the German states between 1993 and 2016." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Nationalekonomi, 1994. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44226.

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Internal migration has frequently been subject of empirical research. This study attempts to find a relationship between international immigration and internal out-migration in all German states, covering the time period between 1993 and 2016. The underlying theories were established by Card et al. (2008), Schlömer (2012), Florida (2002) and Chiswick and Miller (2015). These were used to develop a modified version of the gravity model. The dataset was received from the Federal Statistical Office of Germany (Statistisches Bundesamt). The regressions were executed using a fixed effects model and a pooled OLS as a robustness check. The empirical findings suggest no evidence of a statistically significant effect of international immigration on internal out-migration patterns in the covered period. Control variables suggest policymakers to focus on other factors when the effects of immigration policies on internal out-migration are being considered.
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HE, Ran. "Carry-over and interaction effects of different hand-milking techniques and milkers on milk." Thesis, Uppsala universitet, Statistiska institutionen, 1986. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-154641.

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The main idea of this thesis is studying the importance of the carry-over effects and interaction effects in statistical models. To investigate it, a hand-milking experiment in Burkina Faso was studied. In many no electricity access countries, such as Burkina Faso, the amount of milk and milk compositions are still highly  relying on hand-milking techniques and milkers. Moreover, the time effects also plays a important role in stockbreeding system. Therefore, falling all effects, carry-over effects and interaction effects into a linear mixed effects model, it is concluded that the carry-over effects of milker and hand-milking techniques cannot be neglected, and the interaction effects among hand-milking techniques, different milkers, days and periods can be substantial.
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Maengando, Angshed Sara, and Fluck Vendela von. "An analysis of the determinants of Foreign Direct Investments to OECD countries." Thesis, Södertörns högskola, Nationalekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-38247.

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This study examines the determinants of inward foreign direct investment to OECD countries. The focus is on horizontal FDI. The purpose of the research is to contribute to the ongoing research, and adding value. This is done by using a dynamic perspective of time, and controlling for country-specific characteristics. The thesis uses panel data covering all 36 OECD countries over a 23 year long time period, 1995-2017. Three regressions have been done using a linear fixed effects model, as well as four addition regressions testing the robustness of the results. Earlier studies have received spread results, as have this study. It found market size, economic stability, trade openness, and currency value as significant determinants of the inward flow of FDI to OECD countries.
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Mingolini, Riccardo. "Investimenti in lobby: Un modello per stimare il loro impatto sull'azienda." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13291/.

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In questo elaborato di tesi verrà analizzata l’attitudine di una azienda ad investire in lobbying, misurato attraverso varie variabili importanti per la stessa quali ad esempio il capitale, il reddito netto dell’impresa, il numero degli impiegati (et simila) e il loro impatto scoraggiante o incentivante rispetto alla nostra variabile dipendente. Cercheremo infine di trovare un modello che approssima in modo sostanziale suddette dipendenze e variabili, in modo da tracciare un filo logico e matematico fra la nostra variabile dipendente Y ( investimento in lobbying) e le nostre variabili indipendenti X cioè gli indici e le variabili in valore monetario importanti per definire una azienda e il suo settore di appartenenza (SIC CODE).
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Kamangar, Daniel, and Richard Sundin. "Management and CEO Stock Ownership and its Effect on Company Performance." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229670.

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This is a study on the effect of management and CEO stock ownership on company performance. A regression analysis is performed on panel data consisting of a sample of 30 companies listed on OMX Stockholm Mid Cap. A total of 210 and 2520 observations is considered on a yearly and monthly basis, respectively, for seven years (2010-2016). The Hausman test is applied for determining between the fixed effects and random effects regression models. Results show that management relative stock ownership has a significant positive effect on company net income growth and return on assets. The effect is not significant for CEO stock ownership, which is contrary to what commonly has been shown for large companies in previous research. Moreover, alternative methodology is discussed for the benefit of the future researcher. The authors illustrate how the selection of dummy variables can be vital for final model outcomes, and it is thus an important aspect to consider when performing panel data analysis.
I den här studien undersöks hur aktieinnehav hos ledning och den verkställande direktören i ett företag påverkar företagsutvecklingen. Studien genomförs med regressionsanalys på paneldata som består av 30 företag, samtliga noterade på OMX Stockholm Mid Cap. Totalt samlas 210 och 2520 observationer på årsbasis respektive månadsbasis över sju år (2010-2016). Hausman-testet används för att bestämma vilken av fixed effects-modellen och random effects-modellen som ska användas i regressionen. Resultaten visar att relativt aktieinnehav hos ledningen har en positiv signifikant påverkan på ett företags nettoinkomstutveckling och avkastning på tillgångar. Den verkställande direktörens aktieinnehav visas inte vara signifikant, vilket är motsatt till det som generellt har visats för stora företag i tidigare forskning. Regressionerna genomförs även med alternativa metoder, vilka det resoneras kring i en diskussion som bör vara till gagn för vidare forskning. Författarna illustrerar hur val av dummy-variabler kan ha en avgörande betydelse för regressionsanalysen, och att det således är en viktig aspekt att ta hänsyn till när regressioner genomförs på paneldata.
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Petrovic, Katarina. "Government Debt : Why Has the Government Debt Increased? An Analysis of What Factors Influence the Long-Term Interest Rate?" Thesis, Karlstads universitet, Fakulteten för ekonomi, kommunikation och IT, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-29051.

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This paper analyzes what factors influence the long-term interest rate, in order to give an understanding of why the government debt has increased in EU member states. It is a statistical study of panel data analyzed by the fixed effect model. The research of the 27 EU member states is based on secondary data from the European Commission; Eurostat and EconStats. The results by the fixed effect model show that government debt, budget deficit and presidential system are significant and have a positive relationship with the long- term interest rate. The growth rate is significant, having a negative relationship with the long-term interest rate and the financial crisis did not increase the long-term interest rate. The results were not entirely consistent with theories and previous studies.
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Schanzer-Larsen, Arnold. "The effects of immigration on the income of native born workers: Evidence from Sweden." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54685.

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Abstract  Course: NAA305 Bachelor Thesis in Economics 15 ECTS  University: Mälardalen University, School of Business, Society and Engineering, Västerås  Title: The effects of immigration on the income of native-born workers:  Evidence from Sweden Author: Arnold Schanzer-Larsen  Supervisor: Johan Lindén  Problem: Sweden has experienced a lot of immigration, and the phenomenon has received a great deal of attention in the public and political debate. There is, among other things, fear that immigration could be harmful for the labor market outcome of the receiving country. Researchers from a variety of countries have tried to address this issue by estimating the effect of immigration on the native wage of the receiving country. The results have varied strongly and no universal conclusion can be drawn. For what can be said about Sweden, there is no paper (of our knowledge) that has done any similar estimates. For that reason, it is of great importance that there is some research which could bring empirical evidence and shed light on the debate.  Purpose of the Research: The aim of the thesis is to quantitatively measure immigrations effect on the wage of native workers in Sweden. Methodology:  Conducting a panel study, observation of the average native income from 290 municipalities over 2011-2019 was collected. The effect was estimated using OLS regression technique and a fixed effect model.  Conclusion: From a 10% increase in the share of foreign-born within a municipality, led on average to a 2.89% increase in the native average income in that municipality.  Keywords: Immigration, Income, Wage, Unemployment rate, Panel study, Fixed effect model, Native, Labor market, The equilibrium model, Human capital, Skill-composition
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Books on the topic "Fixed effect model"

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Fixed effects regression models. Thousand Oaks, Calif: Sage Publications, 2009.

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Allison, Paul. Fixed Effects Regression Models. 2455 Teller Road, Thousand Oaks California 91320 United States of America: SAGE Publications, Inc., 2009. http://dx.doi.org/10.4135/9781412993869.

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Linear and nonlinear models: Fixed effects, random effects, and mixed models. Berlin: Walter de Gruyter, 2006.

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Konstantopoulos, Spyros. Fixed and mixed effects models in meta-analysis. Bonn, Germany: IZA, 2006.

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Grafarend, Erik. Linear and Nonlinear Models: Fixed effects, random effects, and total least squares. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Caselli, Paola. Fiscal consolidations under fixed exchange regimes. [Roma]: Banca d'Italia, 1998.

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Blomström, Magnus. Is fixed investment the key to economic growth? Cambridge, MA: National Bureau of Economic Research, 1993.

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Inoue, Atsushi. A portmanteau test for serially correlated errors in fixed effects models. Cambridge, MA: National Bureau of Economic Research, 2005.

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Razin, Assaf. Fixed costs and FDI: The conflicting effects of productivity shocks. Cambridge, MA: National Bureau of Economic Research, 2004.

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Yeom, Namsoo. Effects of asymmetric demand shocks in a fixed exchange rate two-country model. [s.l.]: typescript, 1992.

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Book chapters on the topic "Fixed effect model"

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Piyaratna, Jayasanka, and Jagath C. Rajapakse. "Spatiotemporal Analysis of Functional Images Using the Fixed Effect Model." In Lecture Notes in Computer Science, 190–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45729-1_19.

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Vannucci, Giulia, Anna Gottard, Leonardo Grilli, and Carla Rampichini. "Random effects regression trees for the analysis of INVALSI data." In Proceedings e report, 29–34. Florence: Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-304-8.07.

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Mixed or multilevel models exploit random effects to deal with hierarchical data, where statistical units are clustered in groups and cannot be assumed as independent. Sometimes, the assumption of linear dependence of a response on a set of explanatory variables is not plausible, and model specification becomes a challenging task. Regression trees can be helpful to capture non-linear effects of the predictors. This method was extended to clustered data by modelling the fixed effects with a decision tree while accounting for the random effects with a linear mixed model in a separate step (Hajjem & Larocque, 2011; Sela & Simonoff, 2012). Random effect regression trees are shown to be less sensitive to parametric assumptions and provide improved predictive power compared to linear models with random effects and regression trees without random effects. We propose a new random effect model, called Tree embedded linear mixed model, where the regression function is piecewise-linear, consisting in the sum of a tree component and a linear component. This model can deal with both non-linear and interaction effects and cluster mean dependencies. The proposal is the mixed effect version of the semi-linear regression trees (Vannucci, 2019; Vannucci & Gottard, 2019). Model fitting is obtained by an iterative two-stage estimation procedure, where both the fixed and the random effects are jointly estimated. The proposed model allows a decomposition of the effect of a given predictor within and between clusters. We will show via a simulation study and an application to INVALSI data that these extensions improve the predictive performance of the model in the presence of quasi-linear relationships, avoiding overfitting, and facilitating interpretability.
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Guo, Penghui. "A Study on Dynamic Spatial Fixed Effect Model Based on Endogenous Initial Value." In Computational Risk Management, 515–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18387-4_57.

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Maunder, Mark N., Hans J. Skaug, David A. Fournier, and Simon D. Hoyle. "Comparison of Fixed Effect, Random Effect, and Hierarchical Bayes Estimators for Mark Recapture Data Using AD Model Builder." In Modeling Demographic Processes In Marked Populations, 917–46. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-78151-8_42.

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Liu, Shuhui. "Analysis of the Influence of Financialization on Audit Fees Based on Multidimensional Fixed Effect Model." In Atlantis Highlights in Intelligent Systems, 877–87. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-010-7_88.

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Klette, Tor Jakob, and Frode Johansen. "Accumulation of R&D Capital and Dynamic Firm Performance: a Not-so-Fixed Effect Model." In The Economics and Econometrics of Innovation, 367–97. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4757-3194-1_15.

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Balestra, Pietro. "Fixed Effect Models and Fixed Coefficient Models." In Advanced Studies in Theoretical and Applied Econometrics, 30–45. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-009-0375-3_3.

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Balestra, Pietro. "Fixed Effect Models and Fixed Coefficient Models." In Advanced Studies in Theoretical and Applied Econometrics, 34–49. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-0137-7_3.

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Balazsi, Laszlo, Laszlo Matyas, and Tom Wansbeek. "Fixed Effects Models." In Advanced Studies in Theoretical and Applied Econometrics, 1–34. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60783-2_1.

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Balestra, Pietro, and Jayalakshmi Krishnakumar. "Fixed Effects Models and Fixed Coefficients Models." In Advanced Studies in Theoretical and Applied Econometrics, 23–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-75892-1_2.

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Conference papers on the topic "Fixed effect model"

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Wei, Fang, and Wenxing Li. "Managerial Power and Investment Efficiency——Fixed Effect Model Based on Panel Data." In 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2020. http://dx.doi.org/10.1109/icemme51517.2020.00188.

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Abu Bakar, Nor Mazlina, and Habshah Midi. "The Applications of Robust Estimation in Fixed Effect Panel Data Model." In Proceedings of the 1st Aceh Global Conference (AGC 2018). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/agc-18.2019.54.

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Wu, Qiyuan, Zhong Ma, and Xufan Zhang. "Product Market Competition and R&D Investment Empirical Evidence Based on the Fixed Effect Model." In 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2020. http://dx.doi.org/10.1109/icemme51517.2020.00166.

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Han, Dan, and Yuling Zhao. "Research on Technology Innovation Information Management of High-tech Enterprises Based on Fixed Effect Model." In 2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM). IEEE, 2021. http://dx.doi.org/10.1109/icekim52309.2021.00190.

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Rini, Dyah Setyo, Sigit Nugroho, Dian Agustina, Ratu Eva Febriani, Tommy Jomecho, Diah Permata Syaiful, and Sanita Grasia Rumahorbo. "Spatial panel data model of poverty in Bengkulu province with fixed effect and spatial error autocorrelation." In THE 3RD INTERNATIONAL CONFERENCE ON MATHEMATICS AND SCIENCES (THE 3RD ICMSc): A Brighter Future with Tropical Innovation in the Application of Industry 4.0. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0112039.

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Lawniczak, Anna T., and Shengkun Xie. "Study of number of packets in transit in a data network model near onset of congestion using functional fixed effect models." In 2008 Canadian Conference on Electrical and Computer Engineering - CCECE. IEEE, 2008. http://dx.doi.org/10.1109/ccece.2008.4564851.

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Chen, Dawei, Jiguo Zhang, Jiaguangyi Xiao, and Yong Chen. "Rubbing Of a Bladed Disk Considering Coriolis Effect: A Reduced Model Based on Complex Modal Analysis." In ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gt2021-59008.

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Abstract Due to the high demands of aerodynamic efficiency in modern aero-engines, tip clearances between blades and casings are becoming smaller. This increases the possibility of rubbing between rotating bladed disks and their surrounding casings. Rotational effects exhibit increased significance in the latest generation of fans, which currently have relatively long blade and elongated cantilevered shaft. Previous studies on the rotor dynamics during rub impact have mainly focused on simplified models. However, it is necessary to take both realistic blades and Coriolis effect into account. Based on an open-source bladed disk model, the impact of the Coriolis effect on rub-induced responses is investigated. A two-step model reduction method is adopted by combining the fixed interface reduction and cyclic symmetry reduction. Both centrifugal and gyroscopic effects are incorporated in the numerical model. Complex modal analysis, based on classical Craig-Bampton method, is used to improve the model reduction of the gyroscopic system. The response of a flexible bladed disk to a simplified pulse rubbing force is investigated. With the time and space Fourier transform, a Coriolis-induced frequency split is observed on some nodal diameter lines, which indicates the significance of the Coriolis effect in rub-induced responses. A complex model reduction has been successfully applied to the rub-impact problem of cyclic symmetric bladed disks. Compared with the classical model reduction, the numerical results obtained by complex modal analysis are more reasonable. This lays a solid foundation for further rub-impact research considering rotor dynamics.
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Jauhari, Achmad Faridz, Yoyon K. Suprapto, and Achmad Mauludiyanto. "Data Panel Modelling with Fixed Effect Model (FEM) Approach to Analyze the Influencing Factors of DHF in Pasuruan Regency." In International Conference on Applied Science, Engineering and Social Science. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0009881702240232.

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Haapalainen, Eija, Perttu Laurinen, Juha Röning, and Hannu Kinnunen. "Estimation of Exercise Energy Expenditure Using a Wrist-Worn Accelerometer: A Linear Mixed Model Approach with Fixed-Effect Variable Selection." In 2008 Seventh International Conference on Machine Learning and Applications. IEEE, 2008. http://dx.doi.org/10.1109/icmla.2008.131.

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He, Xiang, and Kam K. Leang. "A New Quasi-Steady In-Ground Effect Model for Rotorcraft Unmanned Aerial Vehicles." In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9025.

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Abstract This paper introduces a new quasi-steady in-ground effect model for rotorcraft unmanned aerial vehicles to predict the aerodynamic behavior when the vehicle’s rotors approach ground plane. The model assumes that the compression of the outflow due to the presence of ground plane induces a change in the induced velocity that can drastically affect the thrust and power output. The new empirical model describes the change in thrust as a function of the distance to an obstacle for a rotor in hover condition. Using blade element theory and the method of image, the model parameters are described in terms of the rotor pitch angle and solidity. Experiments with off-the-shelf, fixed-pitch propellers and 3D-printed variable pitch propellers are carried out to validate the model. Experimental results suggest good agreement with 9.5% root-mean-square error (RMSE) and 97% p-value of statistic significance.
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Reports on the topic "Fixed effect model"

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Morales, Leonardo Fabio, and Eleonora Dávalos. Diffusion of crime control benefits: Forced eradication and coca crops in Colombia. Banco de la República Colombia, November 2022. http://dx.doi.org/10.32468/dtseru.314.

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One explanation for the increasing number of hectares with coca cultivation is that eradication strategies displace coca crops but fail to completely clear affected areas. In the drug policy literature, that dynamic shifting is commonly known as the balloon effect. This study integrates georeferenced agricultural data through spatially explicit econometric models to test the hypothesis that forced eradication displace coca crops. Using annual data for 1,116 contiguous municipalities in Colombia between 2001 and 2015, we estimate a spatial Durbin model with municipal and time fixed effects. Our results suggest that, on average, aerial fumigation in a municipality diffuses the benefits of this crime control strategy to neighboring municipalities.
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Muris, Chris, and Irene Botosaru. Binarization for panel models with fixed effects. The IFS, June 2017. http://dx.doi.org/10.1920/wp.cem.2017.3117.

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Weidner, Martin, and Ivan Fernandez-Val. Fixed effect estimation of large T panel data models. The IFS, October 2017. http://dx.doi.org/10.1920/wp.cem.2017.4217.

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Fernandez-Val, Ivan, and Martin Weidner. Fixed effect estimation of large T panel data models. The IFS, March 2018. http://dx.doi.org/10.1920/wp.cem.2018.2218.

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Vogt, Michael, Lena Boneva (Körber), and Oliver Linton. A semiparametric model for heterogeneous panel data with fixed effects. Institute for Fiscal Studies, January 2013. http://dx.doi.org/10.1920/wp.cem.2013.0213.

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Arkhangelsky, Dmitry, and Guido Imbens. The Role of the Propensity Score in Fixed Effect Models. Cambridge, MA: National Bureau of Economic Research, July 2018. http://dx.doi.org/10.3386/w24814.

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Moon, Hyungsik Roger, and Martin Weidner. Dynamic linear panel regression models with interactive fixed effects. IFS, December 2013. http://dx.doi.org/10.1920/wp.cem.2013.6313.

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Moon, Hyungsik Roger, and Martin Weidner. Dynamic linear panel regression models with interactive fixed effects. IFS, December 2014. http://dx.doi.org/10.1920/wp.cem.2014.4714.

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Weidner, Martin, and Bo E. Honoré. Moment Conditions for Dynamic Panel Logit Models with Fixed Effects. The IFS, July 2020. http://dx.doi.org/10.1920/wp.cem.2020.3820.

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Schling, Maja, Roberto Guerrero Compeán, Nicolás Pazos, Allison Bailey, Katie Arkema, and Mary Ruckelshaus. The Economic Impact of Sargassum: Evidence from the Mexican Coast. Inter-American Development Bank, September 2022. http://dx.doi.org/10.18235/0004470.

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This paper assesses the local economic impact of pelagic Sargassum seaweed washed ashore in tourism-heavy coastal zones in the Mexican State of Quintana Roo. The study relies on a carefully designed Geographic Information Systems (GIS) dataset of monthly observations from 2016 to 2019 for 157 beach segments. The dataset comprises an innovate measure of Sargassum seaweed presence, remotely sensed nighttime light intensity as a proxy of economic growth, as well as information on key infrastructure, sociodemographic and beach characteristics. We apply a fixed-effects regression model that controls for general time trends and unobserved, time-invariant differences across observations. We estimate that the presence of Sargassum in a beach segment reduces nighttime light intensity by 17.5%, representing an approximate 11.6% decrease in gross local product. Considering that impacts of Sargassum on local economic activity may be delayed due to reputational effects, our analysis finds that significant lagged effects can be detected up until 12 months after Sargassum was detected on the shoreline. These effect sizes range between a 5.9 and a 9.9% reduction in gross local product. Various robustness checks, including an adjusted measurement of Sargassum and the consideration of potential spatial correlation across beach segments, indicate that estimated impacts are consistently significant and negative across numerous specifications. For one of most tourism-dependent regions in the world, the recurrent influx is one of the most threatening manifestations of climate change. Our research is the first to robustly quantify the economic impact of Sargassum, and highlights the extent to which economic activity is negatively affected by the accumulation of seaweed and how these effects persist over time. The next important step is for both public and private sectors to invest in forecasting systems and containment strategies as well as engage in cleanup efforts to mitigate severe accumulations, inducing economic resilience in coastal communities.
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