scholarly journals Fixed‐Effect Regressions on Network Data

Econometrica ◽  
2019 ◽  
Vol 87 (5) ◽  
pp. 1543-1560 ◽  
Author(s):  
Koen Jochmans ◽  
Martin Weidner
Keyword(s):  
Regression Model ◽  
Fixed Effects ◽  
Sufficient Conditions ◽  
Value Added ◽  
Network Data ◽  
Data Sets ◽  
Important Special Case ◽  
Valid Inference ◽  
Value Added Models ◽  
Matched Data

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.

Estimation and Inference for Linear Models with Two-Way Fixed Effects and Sparsely Matched Data

2020 ◽  
Vol 102 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Valentin Verdier
Keyword(s):  
Student Achievement ◽  
Instrumental Variables ◽  
Fixed Effects ◽  
Dynamic Models ◽  
Linear Models ◽  
Point Estimation ◽  
Inference Method ◽  
Valid Inference ◽  
Matched Data ◽  
Selection On Unobservables

Models with multiway fixed effects are frequently used to address selection on unobservables. The data used for estimating these models often contain few observations per value of either indexing variable (sparsely matched data). I show that this sparsity has important implications for inference and propose an asymptotically valid inference method based on subsetting. Sparsity also has important implications for point estimation when covariates or instrumental variables are sequentially exogenous (e.g., dynamic models), and I propose a new estimator for these models. Finally, I illustrate these methods by providing estimates of the effect of class size reductions on student achievement.

scholarly journals BioNetLink - An Architecture for Working with Network Data

2014 ◽  
Vol 11 (2) ◽  
pp. 68-79
Author(s):  
Matthias Klapperstück ◽  
Falk Schreiber
Keyword(s):  
Experimental Data ◽  
Biological Networks ◽  
Regulatory Networks ◽  
Large Data ◽  
Biological Data ◽  
Network Data ◽  
Data Sets ◽  
Dynamic Views ◽  
Gene Regulatory ◽  
Multiple Network

Summary The visualization of biological data gained increasing importance in the last years. There is a large number of methods and software tools available that visualize biological data including the combination of measured experimental data and biological networks. With growing size of networks their handling and exploration becomes a challenging task for the user. In addition, scientists also have an interest in not just investigating a single kind of network, but on the combination of different types of networks, such as metabolic, gene regulatory and protein interaction networks. Therefore, fast access, abstract and dynamic views, and intuitive exploratory methods should be provided to search and extract information from the networks. This paper will introduce a conceptual framework for handling and combining multiple network sources that enables abstract viewing and exploration of large data sets including additional experimental data. It will introduce a three-tier structure that links network data to multiple network views, discuss a proof of concept implementation, and shows a specific visualization method for combining metabolic and gene regulatory networks in an example.

scholarly journals Determinants of Firm Performance: Evidence from Romanian Listed Companies

2016 ◽  
Vol 9 (1) ◽  
pp. 53-69 ◽  
Author(s):  
Sebastian Lazăr
Keyword(s):  
Firm Performance ◽  
Fixed Effects ◽  
Value Added ◽  
Listed Companies ◽  
Sales Growth ◽  
Fixed Effects Model ◽  
Resource Based View ◽  
Firm Profitability ◽  
Negative Effect ◽  
Positive Effect

AbstractThe paper investigates firm-specific determinants of firm profitability for Romanian listed companies over the 2000-2011 period within the framework of resource based view of the firm. The results show that tangibles, leverage, size and labour intensity have negative effect on firm performance, while sales growth and value added have a positive effect. The results prove robust when introducing two-way fixed effects model and industry year effects model (in order to simultaneously account for specific industry characteristics and time effects).

GENE SELECTION USING LOGISTIC REGRESSIONS BASED ON AIC, BIC AND MDL CRITERIA

2005 ◽  
Vol 01 (01) ◽  
pp. 129-145 ◽  
Author(s):  
XIAOBO ZHOU ◽  
XIAODONG WANG ◽  
EDWARD R. DOUGHERTY
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Gene Selection ◽  
Information Criterion ◽  
Cancer Classification ◽  
Data Sets ◽  
Classification Methods ◽  
Gene Expressions ◽  
Experimental Conditions

In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables (gene expressions) and the small number of experimental conditions. Many gene-selection and classification methods have been proposed; however most of these treat gene selection and classification separately, and not under the same model. We propose a Bayesian approach to gene selection using the logistic regression model. The Akaike information criterion (AIC), the Bayesian information criterion (BIC) and the minimum description length (MDL) principle are used in constructing the posterior distribution of the chosen genes. The same logistic regression model is then used for cancer classification. Fast implementation issues for these methods are discussed. The proposed methods are tested on several data sets including those arising from hereditary breast cancer, small round blue-cell tumors, lymphoma, and acute leukemia. The experimental results indicate that the proposed methods show high classification accuracies on these data sets. Some robustness and sensitivity properties of the proposed methods are also discussed. Finally, mixing logistic-regression based gene selection with other classification methods and mixing logistic-regression-based classification with other gene-selection methods are considered.

scholarly journals Malpractice Environment vs Direct Litigation: What Drives Nursing Home Exit?

2018 ◽  
Vol 55 ◽  
pp. 004695801878799
Author(s):  
R. Tamara Konetzka ◽  
Hari Sharma ◽  
Jeongyoung Park
Keyword(s):  
Nursing Home ◽  
Nursing Homes ◽  
Fixed Effects ◽  
Online Survey ◽  
Market Competition ◽  
Consumer Welfare ◽  
Data Sets ◽  
For Profit ◽  
The Impact ◽  
The Relationship

An ongoing concern about medical malpractice litigation is that it may induce provider exit, potentially affecting consumer welfare. The nursing home sector is subject to substantial litigation activity but remains generally understudied in terms of the effects of litigation, due perhaps to a paucity of readily available data. In this article, we estimate the association between litigation and nursing home exit (closure or change in ownership), separating the impact of malpractice environment from direct litigation. We use 2 main data sources for this study: Westlaw’s Adverse Filings database (1997-2005) and Online Survey, Certification and Reporting data sets (1997-2005). We use probit models with state and year fixed effects to examine the relationship between litigation and the probability of nursing home closure or change in ownership with and without adjustment for malpractice environment. We examine the relationship on average and also stratify by profit status, chain membership, and market competition. We find that direct litigation against a nursing home has a nonsignificant effect on the probability of closure or change in ownership within the subsequent 2 years. In contrast, the broader malpractice environment has a significant effect on change in ownership, even for nursing homes that have not been sued, but not on closure. Effects are stronger among for-profit and chain facilities and those in more competitive markets. A high-risk malpractice environment is associated with change of ownership of nursing homes regardless of whether they have been directly sued, indicating that it is too blunt an instrument for weeding out low-quality nursing homes.

scholarly journals Bank-specific, Industry-specific and Macroeconomic Determinants of Banks Profitability: Empirical Evidence from Tanzania

2016 ◽  
Vol 3 (2) ◽  
pp. 100 ◽  
Author(s):  
Saganga Mussa Kapaya ◽  
Gwahula Raphael
Keyword(s):  
Regression Model ◽  
Fixed Effects ◽  
Capital Adequacy ◽  
Market Development ◽  
Return On Equity ◽  
Net Interest Margin ◽  
Financial Market Development ◽  
Fixed Effects Regression ◽  
Macroeconomic Determinants ◽  
Loan Losses

The study analyzed effects of bank-specific, industry-specific and macroeconomic determinants on banks profitability. It used a maximum of 350 firm-years, from 52 banks from 1998 to 2010 in Tanzania. It did proxy profitability using return on asset (ROA), return on equity (ROE) and net interest margin (NIM). The static fixed effects regression model indicated that; credit facilities (CFA), capital adequacy (TEA), credit risk (CFR), diversification ratio (DIV), bank risk (BAR) and financial market development (MCAd) were significantly influencing ROA. The dynamic fixed effects regression model indicated that lagged ROA, TEA, loan losses provisions (PLT) and BAR, were significantly influencing ROA.

scholarly journals Macro level analysis of factors contributing to value added: technological changes in European countries

2018 ◽  
Vol 16 (4) ◽  
pp. 417-428
Author(s):  
Larysa Antoniuk ◽  
Nataliia Cherkas
Keyword(s):  
Fixed Effects ◽  
Value Added ◽  
European Countries ◽  
Macro Level ◽  
Eastern European ◽  
Technological Changes ◽  
Random Effects Models ◽  
Currency Depreciation ◽  
Developed Economies ◽  
Eastern European Countries

In conditions of globalization and rapidly growing production fragmentation, generation of value added becomes an ultimate goal and a measure of economic performance. The study provides an analysis of factors contributing to value added at macro level in different European countries. The analysis includes a panel framework covering 27 European countries over the period 2006–2015. In order to investigate the differences across regions, three subsamples are considered, namely, developed economies, PIIGS (Portugal, Italy, Ireland, Greece and Spain) and Central-Eastern European Countries (CEEC). Pooled OLS, fixed effects and random effects models are used. The results indicate that increase of value added corresponds to budget discipline, quality of human capital improvement, strong currency and transparent institutions. It could be expected that currency depreciation improves performance of the value added of exported final goods. However, the results show the opposite evidence: currency depreciation causes the value added decrease in all groups. Thus, for transitional countries, it is im¬portant not only to join global production chains, but also to acquire a significant share in generation of value added in these chains based on technological changes.

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