Appendix Table A1 Number of years since deregulation

Similar documents
Appendix A. Table A1: Marginal effects and elasticities on the export probability

Internet Appendix to. The Price of Street Friends: Social Networks, Informed Trading, and Shareholder Costs. Jie Cai Ralph A.

Panel A: Treated firm matched to one control firm. t + 1 t + 2 t + 3 Total CFO Compensation 5.03% 0.84% 10.27% [0.384] [0.892] [0.

Credit Supply and Monetary Policy: Identifying the Bank Balance-Sheet Channel with Loan Applications. Web Appendix

Internet Appendix for CEO Personal Risk-taking and Corporate Policies TABLE IA.1 Pilot CEOs and Firm Risk (Controlling for High Performance Pay)

The Effects of Presidential Politics on CEO Compensation

Internet Appendix for Does Stock Liquidity Enhance or Impede Firm Innovation? *

DETERMINANTS OF GROWTH

The Financing and Growth of Firms in China and India: Evidence from Capital Markets

Internet Appendix. For. Birds of a feather: Value implications of political alignment between top management and directors

Online Appendix to The Effect of Liquidity on Governance

Online Appendix. for. Female Leadership and Gender Equity: Evidence from Plant Closure

Online Appendix to. Are Two heads Better Than One: Team versus Individual Play in Signaling Games. David C. Cooper and John H.

Appendix A. Table A.1: Logit Estimates for Elasticities

November K. J. Martijn Cremers Lubomir P. Litov Simone M. Sepe

Online Appendix for. To Buy or Not to Buy: Consumer Constraints in the Housing Market

Investment Wines. - Risk Analysis. Prepared by: Michael Shortell & Adiam Woldetensae Date: 06/09/2015

Not to be published - available as an online Appendix only! 1.1 Discussion of Effects of Control Variables

Zeitschrift für Soziologie, Jg., Heft 5, 2015, Online- Anhang

Coffee Price Volatility and Intra-household Labour Supply: Evidence from Vietnam

Business Statistics /82 Spring 2011 Booth School of Business The University of Chicago Final Exam

Table A.1: Use of funds by frequency of ROSCA meetings in 9 research sites (Note multiple answers are allowed per respondent)

Guatemala. 1. Guatemala: Change in food prices

AJAE Appendix: Testing Household-Specific Explanations for the Inverse Productivity Relationship

Gender and Firm-size: Evidence from Africa

Volume 30, Issue 1. Gender and firm-size: Evidence from Africa

Effects of political-economic integration and trade liberalization on exports of Italian Quality Wines Produced in Determined Regions (QWPDR)

Online Appendix to Voluntary Disclosure and Information Asymmetry: Evidence from the 2005 Securities Offering Reform

Tariff vs non tariff barriers in seafood trade

Valuation in the Life Settlements Market

Nuclear reactors construction costs: The role of lead-time, standardization and technological progress

BORDEAUX WINE VINTAGE QUALITY AND THE WEATHER ECONOMETRIC ANALYSIS

Trade Integration and Method of Payments in International Transactions

Structural Reforms and Agricultural Export Performance An Empirical Analysis

Napa Highway 29 Open Wineries

Gasoline Empirical Analysis: Competition Bureau March 2005

1/17/manufacturing-jobs-used-to-pay-really-well-notanymore-e/

Effects of Election Results on Stock Price Performance: Evidence from 1976 to 2008

Preview. Introduction (cont.) Introduction. Comparative Advantage and Opportunity Cost (cont.) Comparative Advantage and Opportunity Cost

Preview. Introduction. Chapter 3. Labor Productivity and Comparative Advantage: The Ricardian Model

Chapter 3. Labor Productivity and Comparative Advantage: The Ricardian Model. Pearson Education Limited All rights reserved.

Chapter 3. Labor Productivity and Comparative Advantage: The Ricardian Model

Preview. Chapter 3. Labor Productivity and Comparative Advantage: The Ricardian Model

ONLINE APPENDIX APPENDIX A. DESCRIPTION OF U.S. NON-FARM PRIVATE SECTORS AND INDUSTRIES

Return to wine: A comparison of the hedonic, repeat sales, and hybrid approaches

Chapter 3 Labor Productivity and Comparative Advantage: The Ricardian Model

Trade Facilitation and Supply Chain Security:

Bank Risk during the Financial Crisis: Do business models matter?

Syndication, Interconnectedness, and Systemic Risk

Economic Losses from Pollution Closure of Clam Harvesting Areas in Machias Bay

Export Spillover and Export Performance in China

The Role of Specific Trade Concerns Raised on TBTs in the Import of Products to the EU, USA and China

The Gravity Equation in International Trade in Services*

Curtis Miller MATH 3080 Final Project pg. 1. The first question asks for an analysis on car data. The data was collected from the Kelly

This appendix tabulates results summarized in Section IV of our paper, and also reports the results of additional tests.

Preview. Introduction. Chapter 3. Labor Productivity and Comparative Advantage: The Ricardian Model

Statistics & Agric.Economics Deptt., Tocklai Experimental Station, Tea Research Association, Jorhat , Assam. ABSTRACT

Update to A Comprehensive Look at the Empirical Performance of Equity Premium Prediction

The Development of the Pan-Pearl River Delta Region and the Interaction Between the Region and Taiwan

Climate change may alter human physical activity patterns

Changes in Comparative Advantage of South Korea and Her Major Trading Countries*

Chapter 3: Labor Productivity and Comparative Advantage: The Ricardian Model

Relationships Among Wine Prices, Ratings, Advertising, and Production: Examining a Giffen Good

Inside the Family Firm: The Role of Families in Succession Decisions and Performance *

Eestimated coefficient. t-value

The Sources of Risk Spillovers among REITs: Asset Similarities and Regional Proximity

ICT Use and Exports. Patricia Kotnik, Eva Hagsten. This is a working draft. Please do not cite or quote without permission of the authors.

"Primary agricultural commodity trade and labour market outcome

Activity 10. Coffee Break. Introduction. Equipment Required. Collecting the Data

Emerging Local Food Systems in the Caribbean and Southern USA July 6, 2014

Preview. Introduction. Chapter 3. Labor Productivity and Comparative Advantage: The Ricardian Model

Red wine consumption in the new world and the old world

Liquidity and Risk Premia in Electricity Futures Markets

Multiple Imputation for Missing Data in KLoSA

Economic crisis and the duration of world wine export Imre FERTŐ

Innovation, appropriation and new firm formation in European regions

Midterm Economics 181 International Trade Fall 2005

This is a repository copy of Poverty and Participation in Twenty-First Century Multicultural Britain.

Long term impacts of facilitating temporary contracts: A comparative analysis of Italy and Spain using birth cohorts

The R&D-patent relationship: An industry perspective

The Bank Lending Channel of Conventional and Unconventional Monetary Policy: A Euro-area bank-level Analysis

Investigating the effect of geographical distances and cultural proximity on the Hungarian wine trade

Ex-Ante Analysis of the Demand for new value added pulse products: A

QUARTELY MAIZE MARKET ANALYSIS & OUTLOOK BULLETIN 1 OF 2015

The Impact of Free Trade Agreement on Trade Flows;

Flexible Working Arrangements, Collaboration, ICT and Innovation

Recent U.S. Trade Patterns (2000-9) PP542. World Trade 1929 versus U.S. Top Trading Partners (Nov 2009) Why Do Countries Trade?

IMPACT OF PRICING POLICY ON DOMESTIC PRICES OF SUGAR IN INDIA

Heat stress increases long-term human migration in rural Pakistan

ECONOMIC IMPACT OF WINE AND VINEYARDS IN NAPA COUNTY

Fair Trade and Free Entry: Can a Disequilibrium Market Serve as a Development Tool? Online Appendix September 2014

Final Exam Financial Data Analysis (6 Credit points/imp Students) March 2, 2006

ICC September 2018 Original: English. Emerging coffee markets: South and East Asia

wine 1 wine 2 wine 3 person person person person person

INSTITUTE AND FACULTY OF ACTUARIES CURRICULUM 2019 SPECIMEN SOLUTIONS. Subject CS1B Actuarial Statistics

Dietary Diversity in Urban and Rural China: An Endogenous Variety Approach

Pitfalls for the Construction of a Welfare Indicator: An Experimental Analysis of the Better Life Index

Can Belgian Firms cope with the Chinese Dragon and the Asian Tigers? The Export Performance of Multiproduct Firms on Foreign Markets

FACTORS DETERMINING UNITED STATES IMPORTS OF COFFEE

STAT 5302 Applied Regression Analysis. Hawkins

Transcription:

Appendix Table A1 Number of years since deregulation This table presents the results of -in-s models incorporating the number of years since deregulation and using data for s with trade flows are above $10 million 1977 dollars. Column 1 shows a Within-OLS model and column 2 a Within-Poisson estimator, both with fixed effects. For the OLS model, ln(trade_share), the log trade share of the destination-state among origin-state s exports, is the dependent variable. For the Poisson model the dependent variable is TRADE_SHARE. The explanatory variables are as follows (indicator variable names are preceded by the prefix D_): ln(gdp_dest) is the destination-state s GDP; ln(wage_dest) is the destinationstate s wage index; D_1993 is equal to one if year is equal to 1993, and zero if it is equal to 1977; DEREG_YEARS D_DEREG (the variable of interest) is the interaction of the number of years since effective deregulation (DEREG_YEARS) with the indicator variable that equals one if the deregulated interstate banking entry as of 1993, and zero otherwise (D_DEREG). The Within model has origin-state clustered standard errors while the Within-Poisson model relies on robust standard errors. t-stats are reported in parentheses below coefficient estimates. *, **, *** denote statistical significance at 10%, 5%, and 1% levels, respectively. Within Within-Poisson 1 2 ln(gdp_dest) 1.0103 *** 0.7640 *** (9.78) (6.36) ln(wage_dest) -0.1376 0.0206 (0.60) (0.06) D_1993-1.1762 *** -1.0171 * (6.04) (4.48) DEREG_YEARS D_DEREG 0.0205 *** 0.0211 *** (4.46) (3.66) Number of observations 3512 3512 Number of std. error clusters 48 robust std. errors Origin-destination fixed effects yes yes Regression F-stat [chi 2 ] 48.25 *** [66.91] *** Within-R 2 0.0986 61

Appendix Table A2 Ex ante for risk-sharing and to trade: Poisson -in-s regressions This table presents the results of -in-s models using Within-Poisson estimators with fixed effects for testing the impact of banking deregulation on trade taking into account the ex ante for risk-sharing and trade. All regressions are with data with trade flows above $10 million 1977 dollars. Columns 1 and 2 show the results for two samples, the s that offered, respectively, the lowest and highest for risk-sharing according to a measure adapted from Acharya, Imbs, and Sturgess (2011), while columns 3 and 4 repeat the exercise for a measure taken from Morgan, Rime, and Strahan (2004). Columns 5 and 6 give the results for two samples split by the in manufacturing proxying for ex ante for intra- trade while columns 7 and 8 present the results for s that were most similar and dissimilar in terms of, respectively. In all columns, TRADE_SHARE, the trade share of the destination-state among origin-state s exports, is the dependent variable. The explanatory variables are as follows (indicator variable names are preceded by the prefix D_): ln(gdp_dest) is the destination-state s GDP; ln(wage_dest) is the destination-state s wage index; D_1993 is equal to one if year is equal to 1993, and zero if it is equal to 1977; D_DEREG is equal to one if the state deregulated interstate banking entry as of 1993, and zero otherwise (as none of the states had deregulated interstate banking entry as of 1977); D_1993 D_DEREG, the interaction of D_1993 with D_DEREG. All models rely on robust standard errors. t-stats are reported in parentheses below coefficient estimates. *, **, *** denote statistical significance at 10%, 5%, and 1% levels, respectively. Acharya, Imbs, and Sturgess (2011) Highest Morgan, Rime, and Strahan (2004) Intra- trade Comparative advantage (Heckscher-Ohlin inter- trade) in in 1 2 3 4 5 6 7 8 ln(gdp_dest) 0.9030 *** 0.7090 *** 0.9777 *** 0.6195 *** 0.6114 *** 0.8952 *** 0.7751 *** 0.7971 *** (7.95) (3.32) (7.13) (3.21) (2.64) (6.72) (4.78) (5.20) ln(wage_dest) -0.0349 0.0116-0.0987-0.0684 0.4807-0.1886 0.5866-1.0774 *** (0.08) (0.02) (0.24) (0.11) (0.83) (0.45) (1.27) (2.75) D_1993-1.1163 *** -0.9723 *** -1.2094 *** -0.7553-1.1019 *** -1.0776 *** -1.449 *** -0.2393 (3.74) (2.94) (4.67) (1.61) (2.74) (3.93) (4.86) (0.96) D_1993 D_DEREG 0.1587 *** 0.1074 * 0.1906 *** 0.0463-0.0059 0.2176 *** 0.1731 *** 0.0078 (3.84) (1.95) (5.36) (0.57) (0.08) (5.49) (3.29) (0.17) Number of obs. 1840 1672 2040 1472 1526 1986 1858 1654 Regression chi 2 99.40 *** 28.67 *** 97.61 *** 16.52 *** 17.40 *** 101.94 *** 50.47 *** 52.15 *** Robust std. errors yes yes yes yes yes yes yes yes Origin-destination FE yes yes yes yes yes yes yes yes 62

Appendix Table A3 Ex ante for risk-sharing and to trade: Poisson-IV regressions This table presents the results of IV-regression models using Poisson estimators with fixed effects for testing the impact of banking integration on trade taking into account the ex ante for risk-sharing and trade. All regressions are with data on s with trade flows above $10 million 1977 dollars. Columns 1 and 2 show the results for two samples, the s that offered, respectively, the lowest and highest for risk-sharing according to a measure adapted from Acharya, Imbs, and Sturgess (2011), while columns 3 and 4 repeat the exercise for a measure taken from Morgan, Rime, and Strahan (2004). Columns 5 and 6 give the results for two samples split by the in manufacturing proxying for ex ante for intra- trade while columns 7 and 8 present the results for s that were most similar and dissimilar in terms of, respectively. In all columns, TRADE_SHARE, the trade share of the destination-state among origin-state s exports, is the dependent variable. The explanatory variables are as follows (indicator variable names are preceded by the prefix D_): ln(gdp_dest) is the destination-state s GDP; ln(wage_dest) is the destination-state s wage index; D_1993 is equal to one if year is equal to 1993, and zero if it is equal to 1977. The endogenous variable BANK_INTEG is the fraction of banking assets owned by out-of-state banks that belong to the other state in a given (i.e., it is the total banking assets owned by state m s banks in state i plus the total banking assets owned by state i s banks in state m, divided by the sum of the banking assets of states i and m). IVs are as in Morgan, Rime, and Strahan (2004): indicator variables that equal one if the origin- (destination-) state has deregulated entry by 1993 and zero otherwise; and the number of years the origin- (destination-) state has deregulated interstate entry. All models rely on origin-state clustered standard errors. t-stats are reported in parentheses below coefficient estimates. *, **, *** denote statistical significance at 10%, 5%, and 1% levels, respectively. Acharya, Imbs, and Sturgess (2011) Highest Morgan, Rime, and Strahan (2004) Intra- trade Comparative advantage (Heckscher-Ohlin inter- trade) in in 1 2 3 4 5 6 7 8 ln(gdp_dest) 0.8542 *** 0.6759 *** 0.9044 *** 0.5885 *** 0.5784 *** 0.8697 *** 0.7446 *** 0.7853 *** (6.93) (3.25) (5.82) (3.37) (2.62) (5.74) (4.64) (5.25) ln(wage_dest) -0.2140-0.1008-0.2616 0.0338 0.4595-0.4195 0.4885-1.0867 *** (0.50) (0.18) (0.63) (0.04) (0.66) (1.23) (1.18) (2.46) D_1993-0.8587 *** -0.7944 ** -0.9038 *** -0.8065 * -1.0662 *** -0.7698 *** -1.2298 *** -0.2290 (3.08) (2.18) (3.61) (1.72) (2.88) (2.88) (4.59) (0.76) BANK_INTEG 9.1664 ** 5.2339 6.6295 *** 21.0854 4.4051 8.9069 *** 4.2757 11.1135 (2.03) (1.23) (2.63) (1.44) (0.36) (4.09) (1.52) (0.89) Number of obs. 1840 1672 2040 1472 1526 1986 1858 1654 Number of clusters 48 48 48 48 48 48 48 48 Clustered std. errors yes yes yes yes yes yes yes yes Origin-destination FE yes yes yes yes yes yes yes yes 63

Appendix Table A4 Non-bank financial integration as of 1977 This table presents the regression model results that take into account ex ante financial integration as of 1977 using data on statepairs with trade flows above $10 million 1977 dollars. State-pairs are split into two samples according to their to have experienced low (columns 1 and 3) or high (columns 2 and 4) net flows prior to 1977 using a measure adapted from Kalemli-Ozcan et al. (2010). Columns 1 and 2 use -in-s Within-Poisson fixed-effects estimators while in columns 3 and 4 use the IV-Poisson estimators with fixed effects. In all columns, TRADE_SHARE, the trade share of the destination-state among origin-state s exports, is the dependent variable. The explanatory variables are as follows (indicator variable names are preceded by the prefix D_): ln(gdp_dest) is the destinationstate s GDP; ln(wage_dest) is the destination-state s wage index; D_1993 is equal to one if year is equal to 1993, and zero if it is equal to 1977; D_DEREG is equal to one if the state deregulated interstate banking entry as of 1993, and zero otherwise (as none of the states had deregulated interstate banking entry as of 1977); D_1993 D_DEREG, the interaction of D_1993 with D_DEREG. The endogenous variable used in columns 3 and 4, BANK_INTEG, is the fraction of banking assets owned by out-of-state banks that belong to the other state in a given (i.e., it is the total banking assets owned by state m s banks in state i plus the total banking assets owned by state i s banks in state m, divided by the sum of the banking assets of states i and m). IVs are as in Morgan, Rime, and Strahan (2004): indicator variables that equal one if the origin- (destination-) state has deregulated entry by 1993 and zero otherwise; and the number of years the origin- (destination-) state has deregulated interstate bank entry. The Within-Poisson models rely on robust standard errors while the IV-Poisson models have origin-state clustered standard errors. t-stats are reported in parentheses below coefficient estimates. *, **, *** denote statistical significance at 10%, 5%, and 1% levels, respectively. Within-Poisson regressions IV-Poisson regressions 1 2 3 4 ln(gdp_dest) 0.8170 *** 0.8201 *** 0.8301 *** 0.6634 *** (5.55) (4.55) (4.75) (4.06) ln(wage_dest) 0.0940 0.1801-0.0667-0.0240 *** (0.21) (0.33) (0.15) (0.04) D_1993-1.1353 *** -1.2266 *** -0.9444 *** -0.8697 ** (3.80) (3.53) (3.54) (2.10) D_1993 D_DEREG 0.1746 *** 0.1086 ** (3.57) (2.15) BANK_INTEG 7.1370 * 13.2009 ** (1.69) (2.38) Number of observations 1812 1700 1812 1700 Number of std. error clusters robust errors robust errors 48 48 Origin-destination FE yes yes yes Yes Regression Chi 2 61.31 *** 45.17 *** 64

Appendix Table A5 Prior Political Economy Links This table presents the results taking into account ex ante political links as of 1977 using data for s with trade flows above $10 million 1977 dollars. State pairs are split into two samples according to the smallest (columns 1 and 3) or largest (columns 2 and 4) dissimilarity in political histories ten years prior to 1977. In columns 5 and 6, results for a sample with Republican-controlled states with smallest political distances are shown. Columns 1, 2 and 5 use -in-s Within Poisson estimators while in columns 3, 4 and 6 use IV-Poisson estimators. All regressions are with fixed effects. In all columns, TRADE_SHARE, the trade share of the destination-state among origin state s exports, is the dependent variable. The explanatory variables are as follows (indicator variable names are preceded by the prefix D_): ln(gdp_dest) is the destination-state s GDP; ln(wage_dest) is the destination-state s wage index; D_1993 is equal to one if year is equal to 1993, and zero if it is equal to 1977; D_DEREG is equal to one if the state deregulated interstate banking entry as of 1993, and zero otherwise (as none of the states had deregulated interstate banking entry as of 1977); D_1993 D_DEREG, the interaction of D_1993 with D_DEREG. The endogenous variable used in columns 3 and 4, BANK_INTEG, is the fraction of banking assets owned by out-of-state banks that belong to the other state in a given state pair (i.e., it is the total banking assets owned by state m s banks in state i plus the total banking assets owned by state i s banks in state m, divided by the sum of the banking assets of state i and m). IVs are as in Morgan, Rime, and Strahan (2004): indicator variables that equal one if the origin (destination) state has deregulated entry by 1993 and zero otherwise; and the number of years the origin (destination) state has deregulated interstate entry. The Within Poisson models rely on robust standard errors while the IV-Poisson models have origin-state clustered standard errors. t-stats are reported in parentheses below coefficient estimates. *, **, *** denote statistical significance at 10%, 5%, and 1% levels, respectively. Within-Poisson regressions Poisson-IV regressions Within-Poisson Poisson-IV political political political political party distance political when Republicans are in power political when Republicans are in power 1 2 3 4 5 6 ln(gdp_dest) 0.7841 *** 0.9153 *** 0.6526 *** 1.0383 *** 0.9917 0.9297 (4.69) (6.55) (4.44) (6.75) (1.21) (1.17) ln(wage_dest) 0.3755-0.4237 0.0723-0.5388-0.1366-0.1555 (0.77) (1.02) (0.16) (1.15) (0.11) (-0.10) D_1993-1.3354 *** -0.8558 ** -0.9151 *** -0.8476 *** -1.1619-1.234 * (4.11) (3.10) (3.16) (2.60) (1.37) (-1.71) BANK_INTEG 0.1265 ** 0.1972 *** 8.8302 * 21.3917 ** -0.0668 28.9771 (2.30) (4.08) (2.30) (2.46) (0.54) (1.29) Number of obs. 1876 1636 1876 1636 370 370 Num. of clusters robust errors robust errors 48 48 robust errors 18 State-pair fixed effects yes yes yes yes yes yes Regression Chi 2 41.98 *** 71.90 *** 28.24 *** 65