Participation of Japanese regional Banks in International Syndicated Loans: Lending

behavior and explanatory factors

Masaki YAMAGUCHI

Yamagata University

Annual Tokyo Business Research Conference, Waseda University, 15-16 December, 2014

Motivation

• Hot issue – international syndicated loans• Gunma Bank – 10 billion yen buildup by the end of FY2013

• Hyakugo Bank – 55 billion yen buildup by the end of FY2015

• Chiba Bank – 20% increase of foreign currency loans by the end of FY2017

• Growth strategies of regional banks• Loan demand cannot be expected to increase amid fierce competition in

shrinking regional economies

• Participation in syndicated loans could serve as a new source of profits for regional banks

Research Questions

1. Characteristics of deals that regional banks participated?

2. Factors which enhance regional banks’ participation ?

Questions

Motivation

Related literature

Analysis 1 Analysis２

Result１ Result２

Related literature

• Type 1： Decision of syndication• Influencing factors on decision whether set up a syndicate or not

• binary-choice model, Syndicate = F (Information, Agency, Loan term)

• Dennis and Mullineaux (2000), Godlewski and Weil (2008)

• Type2: Size of a syndicate• what factors affect the syndicate structure

• count data model, Size = F (Opaque, Loan Characteristics)

• Lee and Mullineaux (2004) , Sufi (2007)

Related literature

• Type 3 : Difference in lending behavior• Difference between bank types

• Model; Spread = F (loan terms, bank types)

• Haselmann and Wachtel (2011), Harjoto, Mullineaux, and Yi (2006)

• Position of this study• close to the first type

• different in research object ; regional banks

Data Source

• Thomson Reuter – DealScan: Loan Database

• Sample: 10,907 deals, Japanese banks participated

• Period: 2009 – Sep. 2014

• Location: All over the world

Japanese banks

Regional banks

League Table: 2009 – Sep. 2014Bank Name

Number ofDeals

Bank NameNumber ofDeals

Bank NameNumber ofDeals

Chiba 80 Fukuoka 4 Kinki Osaka 1

Hachijuni 32 Oita 3 Hokkoku 1

Yamaguchi 26 Hyakujushi 3 Fukui 1

Chugoku 24 Ogaki Kyoritsu 3 Kyoto 1

Shizuoka 18 Tsukuba 3 Hokuto 1

Gunma 16 Akita 3 Shonai 1

Yokohama 12 Higashi-Nippon 2 Michinoku 1

Hiroshima 12 Toho 2 Nishi-Nippon 1

Minato 12 Joyo 2 Aomori 1

Iyo 5 Higo 2 Shiga 1

77 5 Daishi 1 Ashikaga 1

Hyakugo 4 Dasan 1 Keiyo 1

Borrower CountryBorrowercountry

Number ofDeals

Borrowercountry

Number ofDeals

USA 61 UK 5

Korea 17 Vietnam 4

China 12 Sweden 3

India 12 Chile 2

Panama 11 Malaysia 1

HK 10 UAE 1

Thailand 9 Cayman 1

Indonesia 9 Netherland 1

Singapore 8 Brazil 1

Australia 7 Belgium 1

Liberia 6 Canada 1

Mexico 5 Philippines 1

・US takes the top borrower nationality

・83 borrowers from Asian countries

Hypothesis 1: Asian nationality enhances the possibility of regional banks participation

Geographical proximity reduces information asymmetry

CurrencyCurrency

Number ofDeals

Percentage

USD 108 57.1

JPY 61 32.3

CNY 5 2.6

HKD 4 2.1

US Equiv 4 2.1

AUD 3 1.6

Multi 2 1.1

CAD 1 0.5

Euro 1 0.5

・Large share of USD can be partly explained by the borrower nationality

・Hypothesis 2: regional banks prefer to syndicated loans denominated in JPY

Most regional banks have difficulty with funding USD

PurposePurpose

Number ofDeals

Percentage

Corporate purposes 81 42.9

Working capital 43 22.8

Debt Repay 21 11.1

Ship finance 15 7.9

Capital expend 13 6.9

Project finance 6 3.2

CP backup 3 1.6

Takeover 3 1.6

Equip. Purch. 2 1.1

Aircraft 1 0.5

Security Purchase 1 0.5

・Top three loan purposes account for 76.8%

・Capital expenditures, project financing, equipment purchases….difficult to measure the success and failure of long-term projects

・Hypothesis 3: Regional banks avoid taking on such risks

Analysis 1 :Comparison

Participation Non-Participation

Means Sample Means Sample

Loan Size (millions) 355 189 679 10717 0.00

Maturity (years) 4.98 187 4.59 10471 0.04

Number of lenders 10.8 189 11.5 10703 0.00

Regional Bank Regional Bank

U test

Regional banks prefer smaller loans

Participation N on-Participation

N Ratio (%) N Ratio(%)

0 128 10617

1 61 101

0 81 2942

1 108 7776

0 146 10119

1 43 599

0 108 4789

1 81 5929

0 95 5204

1 94 5514

0 162 9686

1 27 1032

0 108 9578

1 81 1140

0 120 9735

1 69 983

Regional B ank Regional B ank

χ2 test

JPY 32.3 0.9 0.00

U SD 57.1 72.6 0.00

W orking C apital 22.8 5.6 0.00

C orp. Purpose 42.9 55.3 0.00

Rating 49.7 51.4 0.64

Financial 36.5 0.0 0.00

G uarantor 14.3 9.6 0.03

Asia 42.9 10.6 0.00

Analysis 2: Probit model

Expalined variable Explanatory variables

Regional banks’ participation ← - Loan Character

1 or 0 log(amount), maturity, rating

currency, guarantor

- Loan Purpose

working capital, corp. purpose

- Borrower Character

country, industry

M odel 1 M odel 2 M odel 3 M odel 4 M odel 5

LAO M O U N T -0.123** -0.123** -0.124** -0.084** -0.082**

(0.026) (0.026) (0.026) (0.028) (0.029)

M ATU RITY -0.003 0.009 0.008 0.013 0.031**

(0.011) (0.011) (0.011) (0.011) (0.011)

RATE 0.155* 0.144 0.161* 0.300** 0.217**

(0.073) (0.074) (0.075) (0.081) (0.083)

JPY 1.924** 1.844** 1.864** 1.847** 1.835**

(0.115) (0.116) (0.117) (0.118) (0.12)

N U M B ER 0.013** 0.015** 0.015** 0.013** 0.014**

(0.003) (0.003) (0.003) (0.003) (0.003)C O RP. -0.072

(0.068)

W O RKIN G 0.525** 0.503** 0.434** 0.407**

(0.097) (0.097) (0.099) (0.102)

G U ARAN TO R 0.197** 0.006

(0.096) (0.103)

ASIA 0.754** 0.663**

(0.081) (0.083)

FIN AN C IAL 0.624**

(0.083)

C O N ST -0.072 -0.222 -0.233 -1.230* -1.423**

(0.482) (0.483) (0.483) (0.527) (0.552)

Sam ple 10643 10643 10643 10643 10643

Pseudo R 2 0.173 0.187 0.189 0.233 0.264

Summary of results• Smaller loans, JPY preference ← funding problem for foreign currencies

• WORKING ← lower risk of project

• ASIA, RATE ← smaller information asymmetry

• Financial ← implicit guarantee

• IFRS Bank ← human resources for overseas transactions

Explanatory variable Marginal effect Explanatory variable Marginal effect

LAOMOUNT -0.001 NUMBER 0.000

MATURITY 0.001 WORKING 0.014

RATE 0.004 ASIA 0.027

JPY 0.262 FINANCIAL 0.024

・JPY produces the greatest effect on the probability of

participation

・ASIA and FINANCIAL have the next strongest marginal

effects