Index

Citation (2020), "Index", de Paula, Á., Tamer, E. and Voia, M.-C. (Ed.) The Econometrics of Networks (Advances in Econometrics, Vol. 42), Emerald Publishing Limited, Bingley, pp. 369-377. https://doi.org/10.1108/S0731-905320200000042019 Publisher: Emerald Publishing Limited Copyright © 2020 Emerald Publishing Limited INDEX Index Note: Page numbers followed by “n” indicate notes. Accelerated failure time model (AFT model), 237 “Activated entities”, 340 Activators, 345–351 Adaptive elastic net GMM method, 32 Adaptive LASSO, 32 Adaptive portfolio risk management approach, 364 Adjacency matrix, 4, 29–30, 32–33 Aggregate equilibrium conditions, 120 adding local links, 123–126 adding self-links, 126–127 aggregation approach, 122–123 Aggregate model specification, 6 Akaike’s information criterion (AIC), 339 Allocation parameters, 122 rule, 86–87 Applied microeconomics, 118 Approximation error, 9 Asian Crisis (1997–1998), 360 Assortative matching, 270 Asymptotic distribution, 66–68, 78–79 Auto loans, 317, 319 Average empty-space distance function, 178 Bank branches in Canada, 176 data, 178–180 disaggregated area analysis, 176 geographical concentration, 177–178 robustness, 188 spatial dependence, 177 spatial panel model, 180–188 Bank of Montreal (BMO), 179 Bank of Nova Scotia, 179 Banking network, 320 Banknote circulation, survival analysis of, 237 clusters, 250–255 hazard model for banknotes, 255–260 network and spatial patterns of banknotes, 243–250 single note inspection data, 237–243 Banknote distribution system (BNDS), 237 Banknote fitness, 243–246 Baseline models, 183–184 Bayesian econometrics, 206 Bayesian information criterion (BIC), 339 Bellman’s equation, 155–156 Bias, 4 Big data, 236 Biological environment, 147 Book and market values of firm, 268–269 Bounded degree, 113 Branch density, 176, 183 Business, 118 Canada, household debt in, 316 Canadian Census, 180 Canadian household debt, 329n1 Canadian Imperial Bank of Commerce (CIBC), 179 Cascades effects, 274–278 Cause spillover effects, 334 Census metropolitan area level (CMA level), 188 Central Limit Theorem (CLT), 17 Centre for Economic Policy Research (CEPR), 358 Chains, 14n4, 20, 22 Change of basis, 28, 35, 52 Chilliwack Forest District, 161 Cholesky decomposition, 128 CISS, 346 Cluster, 178, 251–253 Clustering, 124, 251 Co-author model, 88 Co-stress, 345–351 ID, 340, 350 Coalition-proof Nash equilibrium, 90 Coalitional games, 84 Coast Appraisal Manual (2002), 163, 172 Coauthorship model, 116–120, 132–134 network, 112 Cobb–Douglas utility function, 92 Codes, 117–118 Common correlated effects estimator (CCE estimator), 182 Computational simplifications, 129, 141–142 residual categories of types, 130–131 restriction to observed network types, 129–130 Conditional posterior distributions, 210, 212, 226–229 Confidence region, 123, 127–128 Connectedness by credit market, 325–326 by FI type, 323–325 Connections model, 87 Consumer credit(s), 317 data, 317–318 distributions of consumer loans, 318–320 factors influencing FI-level interconnectedness, 326–328 interconnectedness, 316–317 markets, 318 overlaping portfolio of consumer loans, 320–326 stylized facts, 317 Consumer demographic information, 318 Consumer loans connectedness by credit market, 325–326 connectedness by FI type, 323–325 distributions, 318–320 network construction, 320–321 overall connectedness, 322–323 overlaping portfolio of, 320 Contagion models, 267 Contextual effect, 5 Continuation region, 155 Controlled Markov decision problems, 146 Cooperation structure analysis, 89 Correlated effects, 28 Cosine similarity, 320, 330n14 Cost function, 119 CoVaR approach, 334–335, 337 Credit cards, 317–318 Credit default swap (CDS), 352–356 Credit market, connectedness by, 325–326 Credit unions, 329n10 Cross-holding, 267, 270 matrix and values of organizations, 270–272 Cross-sectional sample selection models (see also Social interactions models) econometric model, 207–209 Markov-chain Monte Carlo estimation, 213 Monte Carlo evidence, 213–221 posterior inference, 209–212 Cross-shareholding relationships, 266–267 Cross-validation, 338–339 Cycle duration, 243–246 Data augmentation, 230–231 Data generating process, 70–75 Data sources method, 171–173 output, 173–174 Dependency matrix, 272 Digital elevation model (DEM), 156–157 Directed graph, 86 Disaggregated area analysis, 176 Disassortative mixing, 270 Disparity filter, 321–322 Distance distance-based measure, 179 function, 251 Disturbance processes, 208 Diversification, 269–270 Division of Financial Stability, 363 Doğan and Taşpinar sampling (DT sampling), 211, 215, 221 Domestic systemically important banks (DSIBs), 316–319 Dot-Com bubble implosion, 350 Double machine learning, 258 Durbin spatial model (DSM), 181 Dynamic demand model, 30 Dynamic geographical information system, 146 Econometric model, 207–209 Economic applications in FRM, 343–364 shock, 334 tail risk management, 336 Edge effects, 173 Efficiency, 11 efficiency–stability tension, 91 Eigenvalues, 34 Elastic net method, 237, 257 Elevated household debt level, 316 Endogenous effects, 5, 28 Endowment realization, 104 Entry and exit, 177 Equal-weighted measure of interconnectedness, 327–328 Estimates, 307–310 Estimation methods, 30, 112 EUCALLOCATION (ArcInfo function), 173 Euclidean distance, 330n14 Euro Area policy makers, 352 European Central Bank (ECB), 190n6 EuroStoxx 50 Volatility Index (VSTOXX), 346 Exogenous effects, 28 Expected utility for n-member market, 104–105 for unreliable complete n-network, 106–107 Faustmann’s rent, 151 Faustmann–Marshall–Pressler solution (FMP solution), 150–152 criticisms, 152–153 Federal Bank Act, 329n10 Financial contagion, 266 book and market values of firm, 268–269 cascades effects, 274–278 effect of cascades of failures, 269 data description, 270–272 diversification, integration, and homophily, 269–270 industry collapse, 278–284 literature review, 267 model, 268–270 network structure, 273–274 results, 273–284 Financial crisis (2008), 336, 362 Financial institutes/institutions (FIs), 236–237, 316, 334, 340–341, 329n4 connectedness by, 323–325 factors influencing FI-level interconnectedness, 326–328 interconnectedness of, 320–321, 324 secondary FIs, 324 Financial Institution File (FIF), 178 cleaning, 203–204 Financial markets, 336, 345, 362–363 Financial networks, 267 Financial risk meter (FRM), 334–335, 340 co-stress, activators and network dynamics, 345–351 computational characteristics, 342–343 and credit default swaps, 352–356 data and computational characteristics, 340 data compilation, 341–342 economic applications, 343 financial institutions, 340–341 implications and extensions, 362–364 modeling framework, 336–340 as predictor of recessions, 356–362 preparation, estimation and reporting algorithm steps, 344 SRM, 351–352 systemic risk measure framework, 336 Financial service companies, 317 Financial stability, 295, 316 Finite payoff depth, 113 Firms, 265–266 Fixed effect elimination, 35 Fixed-coefficient production function, 148–149 Forward Sortation Areas (FSAs), 176 Fraser Timber Supply Area (FTSA), 161 Friendship model, 114–116, 122–123 simulation, 131–132 FRM@Americas, 335, 340, 342, 345, 347–348 FRM macroeconomic risk factors in, 343 FRM@Europe, 340, 342, 345, 347–348 for equity markets, 335 FRM macroeconomic risk factors in, 343 FRM@iTraxx, 356 Eu Senior financials adjacency matrix, 357 Eu Senior financials constituent network total degree of centrality, 359 spillover channel, 358 General risk market movement assessment, 336 Generalized approximate cross-validation criterion (GACV), 334 Generalized cross-validation method, 339 Generalized method of moments (GMM), 190n10 Generic neighborhood effects model, 181–182 Geographic concentrations, 176–178 Geographic information system (GIS), 156–159 Gibbs sampler, 230 Gibbs sampling of parameters of interest, 210–212 Google Trends, 335 Graph, 85–86 Graph-restricted game, 88 Gross domestic product (GDP), 335 Group formation theories, 84 Group-specific fixed effects models with, 35–37, 41–45 models without, 38–41 Hausman specification test, 185 Hazard model for banknotes, 255–260 Heckman models, 232–234 Herfindahl–Hirschman Index (HHI), 319, 327, 330n12 Heterogeneous peer effects, network model with, 5–6 Heterophilic vertices, 72 High co-stress entities, 350 High-dimensional financial network, 336 Home equity lines of credit (Heloc), 318–319 Homophily, 269–270 principle of social network, 62 vertices, 71 Household debt in Canada, 316 indebtedness, 316 Hyper-cube, 128 Identification, 299–301 Industrial concentrations, 176 Information Management System (IMS), 236 Institutional distress, 334 Integration, 268–270 Interbank networks, 306 Interconnectedness, 316–317 of FIs, 320–321 Interpersonal contacts, 84 Inventory management system (IMS), 238 structure of IMS data set, 238–241 Isomorphic subgraphs, 113 Jacobian matrix, 55 JOINITEM (ArcInfo function), 173 Jordan block, 51 Jordan canonical form, 44–45, 51 k-core decomposition algorithm, 328n7 k-fold cross-validation method, 339 K-means clustering method, 251 Kaplan–Meier estimator (KM estimator), 255–256 L1-norm quantile linear regression, 334 LASSO, 32 method, 339 penalization parameter, 337 Latent variables data augmentation, 230–231 deriving conditional distributions of blocks, 225–226 sampling vector of, 210–211 Law of large numbers (LLN), 178 Leave-one-out cross-validation method, 339 Leontief production function, 148 technology, 149 Likelihood, 210 Linderberg central limit theorem, 67 Linear algebra change of basis, 52 Jordan canonical form, 51 Linear independence of matrices, 29–30 Linear quantile Lasso regression, 337 Linear regression model, 327 Linear-in-means model, 4, 14n5 Lines of credit, 317 Link-based SAR, 294, 299 2SLS estimation, 301–303 estimates, 310 identification, 299–301 Linkage costs, 97–98 Loan types, 317 Local economies, 118 Local identification of parameters and Eigenvalues, 57–59 Logistic regression model, 336 Long-term refinancing operations (LTROs), 308 Lumber production, 148–149 Lumber recovery factor (LRF), 149 Machine learning techniques, 112 Macroeconomics, 118 Macroprudential policy making., 362 Macroprudential Research Network (MaRs), 346 Marginal benefit, 151 Market market-aggregated connectedness, 322–323 microstructure, 300 segments, 317 Markit iTraxx CDS indices, 355 Markov chain Monte Carlo algorithm (MCMC algorithm), 123, 206, 213 Markov process, 164 Markov’s inequality, 18 Matrix representation, 291 triangularization, 32, 35, 37, 41 Maximum sustainable yield, 147, 149 Mean squared error (MSE), 251 Method of Payment Survey (MOP Survey), 180 Methods and theory, 118 Minimum spanning tree algorithm, 328n7 Model selection, 257 Moment equation, 65–66, 68–69 Money circulation network, 247–250 market microstructure, 305–306 Monte Carlo evidence, 213 design, 213–215 results, 215–221 Monte Carlo simulation study, 10, 12, 303–305 Mortgage loans, 319 Multigraph, 116 Multiple adjacency-matrix framework, 4–5 Myerson value, 88–89 National Bureau of Economic Research (NBER), 335 recession indicator, 358 “Neighborhood effects” literature, 181–182 Network(s), 83–84 (see also Social network(s)) 2SLS estimator, 8–11 aggregate equilibrium conditions, 120–127 computational simplifications, 129–131 construction, 320–321 cycle duration and banknote fitness, 243–246 of decentralized exchanges, 295–296 formation models, 111 with heterogeneous peer effects, 5–6 identification, 6–8 model misspecification bias, 11–12 models, 4 money circulation network, 247–250 recovered sets, 131–134 reduction algorithm, 328n7 and spatial patterns of banknotes, 243 statistical inference, 127–128 structure, 273–274 type, 113–114 utility and network positions, 113–120 Newly planted forests, 160 Neyman orthogonal moments/scores, 258 Node-based SAR, 294, 297–299 Non-directed graph, 86 Non-distance-based measures, 179 Non-isomorphic subgraphs, 113 Non-linear models, 206 Non-transferable utility, 121 Normalized inverted Wishart sampler, 231 Old-growth forests, 160 Optimal harvesting strategy, 156 Optimal weighting, 70 Ordinary least squares estimator (OLS estimator), 256 Outcome equation, 207 Over-the-counter market (OTC market), 294 Overlaping portfolio of consumer loans, 320–326 Pairwise stability, 89, 96, 120–121 Pairwise stable networks, 97–98 Pareto efficiency, 87 Pareto efficient network, 98–99, 107 Payment system, 305–306 Payments Canada Financial Institution File, 178 geographic concentration, 178–179 industrial concentration, 179 Peer effects model, 4 Penalization parameters, 334 Physical bank branches, 175 Polytope, 127–128 Pooled LASSO estimator, 32 Portfolio diversification, 327 similarity, 320, 329n7 Post-crisis, 363 Posterior inference, 209 Gibbs sampling of parameters of interest, 210–212 likelihood and conditional posterior distributions, 210 priors, 209–210 Pre-crisis, 363 Predicted type shares, 122 Preference classes, 122 Priors, 209–210, 224 Probability, 93–94 of adjacency matrix, 71 PRT approach, 112–113, 120, 122 Pseudocode of financial contagion model, 292 Quadratic programing problem (QP problem), 112, 123, 127–128 Quantile regression, 334–339 Quasi-Maximum Likelihood Estimator, 301 R software, 336 Racial segregation, 111–112 Real GDP, 335 Real Time Gross Settlement Payment System (RTGS Payment System), 305 Recapitalizations, 336 Recession FRM as predictor of, 356 probabilities provision, 336 probability indicators, 335 Recursive methods, 146 Recursive solution via method of dynamic programing, 153 (see also Stochastic dynamic programing) assumptions concerning economic and physical environment, 153–154 Bellman’s equation, 155–156 solution strategy, 154–155 Reflection problem, 28 Regenerative, optimal-stopping problem, 154 Regional distribution center (RDC), 237 Regional distribution point (RDP), 237 Regression results, 193–200 tree analysis, 119 Rent extraction, 149–150 Repayment schedule, 318 Researcher utility, 116 Residential loan, 328 Ridge regression, 257 Robustness, 188 Royal Bank of Canada (RBC), 179 Sample moment equation, 66 selection, 62–63 Secondary FIs, 316 Secured loans, 318 Selection equation, 207 “Shadow banking system”, 363 Shapley value, 88 Simulation parameters, 272 Single note inspection data, 237 institutional background, 237 sample description, 241–243 structure of IMS data set, 238–241 Site heterogeneity, 150 Site index, 168n9 Six-degree separation theory, 62 Size-weighted measure of interconnectedness, 327–328 Slope factor, 172 Smoothed recession probability, 335 Snowball sampling, 61–62, 64 Social interactions models, 28 basic assumptions, 33–34 estimation literature, 32–33 identification literature and proposed methods, 28–32 identification methods for, 28 long panel identification, 35–37 notation, 34 short panel identification, 37–46 Social network(s) (see also Trade networks) for economic behavior, 84 empirical application, 75–77 estimation, 65–70 setup, 64 simulation, 70–75 Society for Worldwide Interbank Financial Telecommunication (SWIFT), 307 Solution concept, 121 Sovereign risk meter (SRM), 345, 351–352 Spatial autocorrelation, 180 parameter, 231–232 Spatial autoregressive model (SAR model), 4, 181, 294 Spatial competition of rival banks, 187–188 Spatial dependence, 177 Spatial Durbin dynamic panel model, 30 Spatial error model (SEM), 33, 181 Spatial geographic concentration, 187 Spatial market structure, 186–187 Spatial or network interdependence, 206 Spatial panel model, 180 banks, 184–187 baseline models, 183–184 big five and small banks, 187–188 Spatial socioeconomics, 185–186 Spillover effects, 295 empirical example, 305–310 link-based SAR, 299–303 Monte Carlo study, 303–305 network of decentralized exchanges, 295–296 node-based SAR, 297–299 SRM@EuroArea, 335, 345, 351 constituent network total degree of centrality, 354–355 Stability, 90–92, 121 Standard community-finding algorithm, 118 Standard deviation (SD), 215 Standard FRM, 335 Statistical inference, 127–128 Statistics Canada Catographic Boundary File, 180 Stochastic block model, 70–73 Stochastic dynamic programing, 146 computational issues, 164–165 data set, 161–164 geographical, intertemporal, and stochastic model, 153–156 GIS, 156–159 illustrative results, 165–166 implementation, 161–166 modeling growth and yield in stands of timber, 160–161 theoretical structure, 147–153 Stopping region, 155 Strategic mortgage defaults, 329n8 Strategic network formation theories, 84 Strategy space, 86 Strength of strong ties, 99–101 of tie, 94 of weak ties, 84 Strong Nash equilibrium, 90 Structurally distinct network positions, 112 Structurally similar network positions, 112 Stumpage rate, 149–150 Subsample of social network data, 73–75 Superintendence of Companies, Securities and Insurance of Ecuador (SUPERCIAS), 266, 270 Symmetric labor market model, 92 Systemic risk, 334–336 FRM systemic risk measure framework, 336–340 Tail dependencies, 336 Tail Event NETwork risk approach (TENET risk approach), 334 TARGET2, 305, 307 Ties strategic establishment, 94–99 strength, 94 strength of strong ties, 99–101 Timber supply area (TSA), 153 Toronto Dominion (TD), 179 Trade example, 88 Trade networks, 92 (see also Social network(s)) basic setup, 92–93 examples, 87–88 imperfect reliability of links, 93–94 literature, 88–92 network formation game, 85–87 strategic establishment of ties, 94–99 strength of strong ties, 99–101 Tree and Stand Simulator (TASS), 160–161 Tree Farm Licenses (TFL), 153 Tree-indexed Markov chain, 7, 14n4, 22 Truncated multivariate normal equation (TMVN equation), 210 Tuned random walk metropolis-Hastings sampler, 232 Tuning parameters, 257 Two-stage least squares estimators (2SLS estimators), 4, 8, 301–303 asymptotic properties, 9–10 finite sample performance, 10–11 Two-step identification strategy, 30 LASSO regression, 33 Two-way fixed effects, 180 Type shares, 114 Umbrella Movement, 63, 75 Unemployment disparities, 182 Uniformly bounded in absolute value (UB), 17 Utility and network positions, 113 coauthorship model, 116–120 friendship model, 114–116 Value at Risk (VaR), 334, 337 Valued graphs, 102n9 Variable Density Yield Prediction (VDYP), 161 Variance–covariance matrix, 209 of idiosyncratic error, 231 Vertices of graph, 85 Voluntary networking, 85 Walrasian equilibrium allocation, 93, 104 Yield curve slope based predictor, 335 Book Chapters Prelims Section 1 Identification of Network Models Chapter 1: Identification and Estimation of Network models with Heterogeneous Interactions Chapter 2: Identification Methods for Social Interactions Models with Unknown Networks Chapter 3: Snowball Sampling and Sample Selection in a Social Network Section 2 Network Formation Chapter 4: Trade Networks and the Strength of Strong Ties Chapter 5: Application and Computation of a Flexible Class of Network Formation Models Section 3 Networks and Spatial Econometrics Chapter 6: Implementing Faustmann–Marshall–Pressler at Scale: Stochastic Dynamic Programing in Space Chapter 7: A Spatial Panel Model of Bank Branches in Canada Chapter 8: Full-information Bayesian Estimation of Cross-sectional Sample Selection Models Chapter 9: Survival Analysis of Bank Note Circulation: Fitness, Network Structure, and Machine Learning Section 4 Applications of Financial Networks Chapter 10: Financial Contagion in Cross-holdings Networks: The Case of Ecuador Chapter 11: Estimating Spillover Effects with Bilateral Outcomes Chapter 12: Interconnectedness through the Lens of Consumer Credit Markets Chapter 13: FRM Financial Risk Meter Index

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