Title page 1

Contents 4

Abbreviations 10

Acknowledgments 12

About the Editors 13

About the Authors 15

Preface 22

Overview 24

PART I. Business Digitalization 37

1. Unintended Consequences of Business Digitalization Among MSMEs During the COVID-19 Pandemic: The Case of the Philippines 38

1.1. Introduction 38

1.2. Philippine MSME Landscape and COVID-19 Impact 40

1.3. Empirical Method 42

1.4. Data 49

1.5. Estimation Results 55

1.6. Conclusion 61

References 63

2. Digital Lifeline? Internet Utilization and Entrepreneurial Resilience in Pandemic Times: The Case of Indonesia 66

2.1. Background 66

2.2. Literature Review 69

2.3. Methodology and Data 71

2.4. Empirical Results 76

2.5. Conclusion and Policy Implications 91

References 93

PART II. Gender-Balanced Growth 97

3. Resilience to Shocks of Micro, Small, and Medium-Sized Enterprises in Fiji 98

3.1. Introduction 98

3.2. Background and Context 102

3.3. Data and Descriptive Evidence 105

3.4. Methodology 115

3.5. Results 119

3.6. Discussion 125

3.7. Conclusion 127

References 129

Appendix 132

4. Women-Led Firms, Digital Technology Adoption, and Access to Finance in India 134

4.1. Introduction 134

4.2. Literature Review 137

4.3. Data and Variable Description 140

4.4. Methodology 146

4.5. Estimation 147

4.6. Robustness Checks 152

4.7. Conclusion and Policy Recommendations 155

References 157

Appendix A4 162

PART III. Entrepreneurship Development 163

5. What Factors Encourage the Entrepreneurial Spirit? Findings from Three Pacific Islands 164

5.1. Introduction 164

5.2. Literature Review 165

5.3. Methodology 168

5.4. Results 168

5.5. Discussion and Implications 178

5.6. Conclusion 183

References 184

6. Individual and Social Preferences of Entrepreneurs: A Study Using Experimental and Nonexperimental Data from Delhi, India 187

6.1. Introduction 187

6.2. Institutional Setting and Data 192

6.3. Artifactual Field Experiments 198

6.4. Empirical Strategy 202

6.5. Empirical Results 204

6.6. Conclusion 216

References 219

PART IV. Innovative Financing Models 223

7. Equivalence of Carbon Tax, Carbon Pricing, and Small and Medium-Sized Enterprise Green Policies 224

7.1. Portfolio Allocation by Considering Environmental, Social, and Governance Scores 224

7.2. Carbon Pricing to Regain Optimal Portfolio Allocation 229

7.3. Diversified Carbon Pricing 231

7.4. Green Bonds 233

7.5. Proposed Solution to Account for Differences 234

7.6/7.7. Small Share of Green Bonds to Total Bond Issuance 240

7.7/7.8. Comparison of Carbon Finance Instruments: Burdens and Recipients 242

7.8/7.9. Implications for Asia's Policymakers 243

7.9/7.10. Conclusion 244

References 246

8. Prospects and Challenges of Digital Invoice Financing for MSMEs in India: An Empirical Study 248

8.1. Introduction 248

8.2. Supply Chain Financing and Role of Digital Invoice Financing for MSMEs 250

8.3. Indian Experiment in Digital Invoice Financing: Some Stylized Facts 252

8.4. Tests of Hypothesis 253

8.5. Data and Methodology 258

8.6. Empirical Analysis and Findings 259

8.7. Major Findings and Recommendations 266

8.8. Concluding Remarks 268

References 270

PART V. Evidence-Based Policy Actions 274

9. Strategies and Resilience of Firms Facing Competition from the Informal Sector 275

9.1. Introduction 275

9.2. Theoretical Perspectives on Informal Sector Competition 277

9.3. Methodology 280

9.4. Data and Variables 282

9.5. Results 283

9.6. Conclusion and Policy Recommendations 292

References 294

Appendix 300

10. Designing a Country's SME Development Index Using Firm-Level Data: The Case of Thailand 308

10.1. Introduction 308

10.2. Thailand's MSME Landscape and Policy Support Measures 310

10.3. Empirical Approaches 312

10.4. Data 312

10.5. Estimation Results 315

10.6. Key Findings from Empirical Analyses and Policy Implication 342

10.7. Conclusion 344

References 345

Appendix 1. Probabilistic Principal Component Analysis Concept 346

Appendix 2. Factor Loadings Based on Probabilistic Principal Component Analysis 351

11. Conclusion: Policy Actions to Build an Optimal MSME Ecosystem 376

Table 1.1. Mean Attributes and Business Performance of MSMEs Using or Not Using the Internet-Based on March 2020 Samples 52

Table 1.2. Mean Attributes and Business Performance of MSMEs Using or Not Using the Internet-Based on August 2020 Samples 53

Table 1.3. Mean Attributes and Business Performance of MSMEs Using or Not Using the Internet-Based on March 2021 Samples 54

Table 1.4. Regression Results of Effects of Using the Internet on Business Performance-Based on the Samples from the March 2020 Dataset 55

Table 1.5. Regression Results of Effects of Using the Internet on Business Performance-Based on the Samples from the August 2020 Dataset 57

Table 1.6. Regression Results of Effects of Using the Internet on Business Performance-Based on the Samples from the March 2021 Dataset 58

Table 2.1. Descriptive Statistics of Entrepreneurs' Characteristics Used in Analysis 75

Table 2.2. Determinants of Internet Use: Logit Estimates 77

Table 2.3. Average Treatment Effect of the Treated of Internet Use on Entrepreneurial Resilience 79

Table 2.4. Balance Assessment Before and After Matching 81

Table 2.5. E-value of Average Treatment Effect of the Treated Estimates 85

Table 2.6. ATT of Internet Utilization on Entrepreneurial Resilience Using Unmatched Data 86

Table 2.7. Simulation-based Average Treatment Effect of the Treated of Internet Utilization on Entrepreneurial Resilience Using Matched Data 87

Table 2.8. Heterogeneous Effect of Internet Use on Entrepreneurial Resilience Across Formal and Informal Entrepreneurs 88

Table 2.9. Heterogeneous Effect of Internet Use on Entrepreneurial Resilience Across Years 91

Table 3.1. Characteristics of MSMEs by Concessional Loan Access 110

Table 3.2. Is the Enterprise Exposed to a Natural Hazard That Could Shut the Business for 4 Weeks? 114

Table 3.3. Did Concessional Loans Aid Post-Pandemic Recovery? (Ordinary Least Squares Analysis) 120

Table 3.4. Did Concessional Loans Aid Post-Pandemic Recovery? (Ordinary Least Squares Analysis-Female) 120

Table 3.5. Did Concessional Loans Aid Post-Pandemic Recovery? (Propensity Score Matching Analysis) 121

Table 3.6. Did Concessional Loans Aid Post-Pandemic Recovery? (Propensity Score Matching Analysis-Female) 121

Table 3.7. Does Past Experience with Climate Shocks Affect Enterprises' Future Responses? (Ordinary Least Squares Analysis) 123

Table 3.8. Does Past Experience with Climate Shocks Affect Enterprises' Future Responses? (Ordinary Least Squares Analysis-Female) 123

Table 3.9. Does Past Experience with Climate Shocks Affect Enterprises' Future Responses? (Propensity Score Matching Analysis) 124

Table 3.10. Does Past Experience with Climate Shocks Affect Enterprises' Future Responses? (Propensity Score Matching Analysis-Female) 124

Table 4.1. Descriptive Statistics 143

Table 4.2. Pooled Analysis of Regression Results from Ordered Probit Models 148

Table 4.3. Regression Results from Ordered Probit Models with Two Different Dependent Variables on Digital Technology Usage 150

Table 4.4. Regression Results from IVProbit Using Binary Dependent Variable Credit Constraint Dummy 154

Table 5.1. Factor Loadings and Correlation Matrices 170

Table 5.2. Key Variables and Covariates by Country (Actual Data) 172

Table 5.3. Key Variables and Covariates by Country (Standardized Data) 173

Table 5.4. Linear Regression Outputs-Attitude and Social Norms 175

Table 5.5. Linear Regression Outputs-Country Estimates 177

Table 6.1. Types of Entrepreneurs in Our Study 197

Table 6.2. Survey Timing and Data Distribution 197

Table 6.3. Intertemporal Choice Sets in the Convex Time Budget Experiment 201

Table 6.4. Socioeconomic Background of the Sample Entrepreneurs 206

Table 6.5. Responses to General Social Survey Trust Questions 207

Table 6.6. Choices in Business Management Diagnostic Test 209

Table 6.7. Estimation Results Based on the Convex Time Budget Model by Andreoni and Sprenger (2012) 213

Table 6.8. Performance and Characteristics of Sample Firms 215

Table 7.1. Rating Methods of Various Rating Agencies 226

Table 7.2. Empirical Analysis of the Relationship Between ESG Scores and Return/Risk 228

Table 7.3. Carbon Price 231

Table 7.4. Scope 1, 2, and 3 Emissions 236

Table 7.5. Examples of Credit Scoring, GHG Tax, and Green Bonds Based on GHG Emissions 238

Table 7.6. Eligible Green Project Categories 241

Table 7.7. Green Bonds as a Percentage of Overall Bond Market 242

Table 7.8. Comparison of Carbon Finance Instruments 242

Table 8.1. Independent Variable Definitions 254

Table 8.2. Descriptive Statistics 259

Table 8.3. Estimation Results of Ordinary Least Squares: Determinants of Interest Rate for Fintech Factoring Financing 260

Table 8.4. Tobit Regression: Determinants of Financier Participation in Fintech Factoring Financing 263

Table 8.5. Comparison of Empirical Results and Major Findings 266

Table 9.1. Adjusted Odds Ratio Obtained from Ordered Logistic Regression-Strategies for Firms Facing Informal Sector Competition 286

Table 10.1. MSME Data in Thailand 313

Table 10.2. Factor Loadings Based on Probabilistic Principal Component Analysis-Total Micro, Small, and Medium-Sized Enterprise Data 318

Table 10.3. Factor Loadings Based on Probabilistic Principal Component Analysis-Wholesale Trade 323

Table 10.4. Factor Loadings Based on Probabilistic Principal Component Analysis-Bangkok (Capital City) 327

Table 10.5. Factor Loadings Based on Probabilistic Principal Component Analysis-Raw Data 339

Table 11.1. New United States Tariffs and Their Potential Impact on MSME Exports in Developing Asia (as of 14 April 2025) 386

4. Women-Led Firms, Digital Technology Adoption, and Access to Finance in India 162

Table A4. Variable Description 162

9. Strategies and Resilience of Firms Facing Competition from the Informal Sector 300

Table A1. Descriptive Statistics 300

Table A2. Variable Descriptions 301

Table A3. Adjusted odds Ratio Obtained from Ordered Logistic Regression-External Factors Affecting Firms 302

Table A4. Adjusted Odds Ratio Obtained from Ordered Logistic Regression-Strategies for Firms in Manufacturing and Services Facing... 303

Table A5. Adjusted Odds Ratio Obtained from Ordered Logistic Regression-Strategies for Small and Medium-sized Firms Facing... 305

Table A6. Adjusted Odds Ratio Obtained from Ordered Logistic Regression-Strategies for Firms Facing Informal Sector Competition;... 306

Table A7. Adjusted Odds Ratio Obtained from Ordered Logistic Regression-Strategies for Firms Facing Informal Sector Competition;... 307

10. Designing a Country's SME Development Index Using Firm-Level Data: The Case of Thailand 352

A1. Factor Loadings (Manufacturing and Bangkok) 352

A2. Factor Loadings (Manufacturing and Outside Bangkok) 355

B1. Factor Loadings (Agriculture and Bangkok) 358

B2. Factor Loadings (Agriculture and Outside Bangkok) 361

C1. Factor Loadings (Real Variables) 364

C2. Factor Loadings (Financial Variables) 367

D1. Factor Loadings (Small Sample Exercise-50% Sample) 370

D2. Factor Loadings (Small Sample Exercise -10% Sample) 373