Abstract

The Global Informal Workforce is a fresh look at the informal economy around the world and its impact on the macroeconomy. The book covers interactions between the informal economy, labor and product markets, gender equality, fiscal institutions and outcomes, social protection, and financial inclusion. Informality is a widespread and persistent phenomenon that affects how fast economies can grow, develop, and provide decent economic opportunities for their populations. The COVID-19 pandemic has helped to uncover the vulnerabilities of the informal workforce.

Index

A

  • Acemoglu, D., 95, 227

  • Actual labor force, official labor force discrepancy with, 23

  • Administrative barriers, 78n9, 79

  • Administrative processes, streamlining, 105

  • Adom, A. D., 95, 223, 233

  • Advanced economies

    • G2P transfers in, 275, 276

    • MIMIC model for, 36t, 41t

  • Africa. See specific topics

  • Agent network coverage, in G2P transfers, 292

  • Agriculture, in sub-Saharan Africa, 117

  • Ahmad, Ehtisham, 8, 256, 269, 270

  • Ahn, J., 159n12, 162

  • Aiyar, S. C., 318

  • Alam, Z., 318–19, 328, 336–37

  • Alesina, A., 122

  • Allen, F., 350, 352

  • Alm, J., 49

  • Alper, E., 298

  • Altonji, J., 169

  • Anand, R., 146, 162

  • Area-based taxes, 270

  • Argentina, 153, 157

  • Asia. See also specific countries

    • factor allocation in, 128

    • firm growth in developing, 116, 118f

    • firm size in, 117, 118f, 119f, 139f

    • land allocation in, 122f, 141f

    • land markets in developing, 117, 122f

    • productivity in, 117, 118f

    • summary statistics for, 137t

  • ATMs, 293, 294

  • Auxilio Emergencial, 281

  • Ayyagari, M. T., 318

B

  • Balance sheets

    • borrower individuals and, 372–74, 375t, 376t

    • empirical models, 373

    • empirical results, 373

    • financial inclusion and, 372–76

    • variables, 372–76

    • weaknesses, 351

    • from World Bank Enterprise Survey, 117

  • Ball, L., 159

  • Baltic countries, shadow economy in, 22t, 48, 49f

  • Bank accounts, 359

    • bank competition and, 360t, 361t

    • individuals without, 359, 365

  • Bank competition

    • bank accounts and, 360t, 361t, 370t

    • credit cards and, 350, 358, 368t, 369t, 372t

    • debit cards and, 350, 359, 366t, 367t, 371t

  • Barro, R. J., 95

  • Bayesian setups, 37

  • Beck, T., 318

  • Benchmarking, 26, 27, 27n18, 28

  • Ben Hassine, M., 319

  • Benin, 202

  • Berger, S., 171

  • Betcherman, G., 146

  • Billetera Móvil (BiM), 289, 306t

  • Birinci, S., 91

  • Blackden, M., 200–01

  • Black economy, 11, 87

  • Blockchain technology, 88n3, 256, 269, 270

  • Boko Haram, 133

  • Bono Independiente, 281

  • Boone indicator, 350, 355, 357–59, 362, 371

    • data from, 354t, 356t

  • Borjas, G., 169–71, 177, 179, 185

  • Borrowing, 268, 323, 324, 324f, 326, 334–36, 338, 351, 358, 372–74

  • Bosch, M., 146

  • Brazil, 145n2, 153, 155, 157, 281

  • Breusch, T., 28, 134

  • Bribes, 231

  • Brosio, G., 270

  • Brunei Darussalam, 100

  • Bryant, J., 170

  • Buehn, A., 25, 49, 90–91

  • Burundi, 37

  • Business cycle, labor informality and, 146, 157, 162–64

  • Business environment, 123, 185, 224, 227–30

C

  • Calomiris, C. W., 318

  • Cameroon, 168, 169, 176, 179

    • stylized facts for, 168, 186f, 187f

  • Capital ratios, 351, 352, 373, 374

    • in sub-Saharan Africa, 351, 352, 374n8

  • Card, D., 169, 170

  • Care work, 197, 200, 203, 207

  • Caribbean, shadow economy in, 41

  • Cash economy, 11

  • Cash-in/cash-out (CICO) networks, G2P transfers and, 294

  • Castillo, P. B., 146

  • CCE. See Common correlated effects

  • CDA. See Currency demand approach

  • C-efficiency VAT measure, 234, 236

  • Central America, labor productivity in, 147

  • Chad, 197

  • Chiapas, 254, 259

  • Childbearing, 199, 202, 203, 212

  • Chile, 147, 155, 157

  • China, 254, 255, 263, 265–69, 271, 272, 318

    • informality in, 255, 266

    • property taxes in, 272

    • SDGs and, 272

    • structural reforms in, 263–64

    • tax reforms in, 255, 263–66

    • VATs in, 254, 265–66

  • Chongqing, 267, 268

  • CICO networks. See Cash-in/cash-out networks

  • C5 indicator, 350, 355, 359, 362

    • data from, 354

  • CIS. See Commonwealth of Independent States

  • Cizel, J., 336

  • Classic criminal activities, 13n4

  • Colombia, 146, 153, 155, 288, 294

  • Commodity price shocks, impulse response function for, 163, 164f

  • Common correlated effects (CCE), 158

  • Commonwealth of Independent States (CIS), 71

    • shadow economy in, 72–76

  • Company manager surveys, shadow economy and, 14, 22–23

  • Competition

    • bank, 349, 350, 355, 357–59, 360t, 361t, 365, 366t, 367t, 368t, 369t, 370t, 371, 372t

    • empirical models, 358–59

    • financial inclusion and, 350, 358–72

    • in sub-Saharan Africa, 357–72

    • of women, 197, 200–204

  • Consumption, real income linked to, 172

  • Corruption, 31, 32, 51, 76, 87, 117, 136, 231, 300

    • in EU, 79

    • in institutional quality, 236

    • as institutional variable, 238

    • measurement of, 124n4

    • shadow economy and, 15t, 76

  • COVID-19 crisis, 275, 288, 295

    • G2P transfers in, 275

    • informal workers impacted by, 72, 81n13, 271

    • population in need of support in, 277f

    • shadow economy during, 72, 81

    • in sub-Saharan Africa, 276f, 297

  • Credit access, 121, 130

    • factor allocation and, 130–32

    • in sub-Saharan Africa, 130–32

    • for women, 206

  • Credit cards, 349

    • bank competition and, 350, 358, 368t, 369t, 372t

  • Cryptocurrencies, 88n3

  • Cuba, 170

  • Currency demand approach (CDA), 23, 24

    • double counting problem in, 30

    • for shadow economy, 14, 30, 47, 50, 51

    • structured hybrid model-based estimation, 14, 28–30

  • Cybersecurity, in G2P transfers, 300

  • Czech Republic, 46, 49

D

  • Dakar, 270, 272

  • Data

    • from Boone indicator, 350, 354t, 356t

    • from C5 indicator, 354

    • collection of, 18, 74, 105, 304

    • on economic development, 87–88, 105

    • on financial inclusion, 352–53, 354t

    • from Financial Soundness Indicators Database, 353–54

    • from Global Financial Development Database, 352, 355, 356t

    • from Global Findex Database, 316, 319, 352–53

    • from H-statistic, 355–56

    • on immigration, 179–80

    • on informality, 153n6, 234

    • on institutional variables, 224

    • on institutions, 240t

    • from Lerner index, 357

    • microdata from Senegal, 192

    • processing, 74–75

    • on sub-Saharan Africa, 116–17, 353–54, 357, 358

  • David, Antonio C., 7

  • Davidovic, Sonja, 8

  • Debit cards, 349

    • bank competition and, 350, 359, 366t, 367t, 371t

  • Decennial Censuses and Surveys, 174

  • Degryse, H., 355

  • Deindustrialization, of sub-Saharan Africa, 115

  • Del Carpio, X., 170

  • Deléchat, Corinne, 8, 336, 352

  • Dell’Anno, R., 27n18

  • Demand instruments, 328n8

  • Demand-side macroprudential policies, 328, 332, 336

  • Demographics. See also Population

    • of education, 200f

    • of entrepreneurship, 176f

    • of Nigeria, 133

    • in sub-Saharan Africa, 116–17

  • De Soto, H., 116

  • Deterrence, shadow economy and, 16t

  • Developing countries. See also Emerging markets

    • MIMIC model for, 33t, 35t, 40t

  • DGE. See Dynamic general equilibrium

  • Digital economy, 88n3, 105

  • Digital fraud, in G2P transfers, 299, 300

  • Digital government, in G2P transfers, 289–91

  • Digital platforms. See also specific topics

  • direct estimation approaches

  • Discrimination, against women, 191, 193, 197, 206, 208, 212, 213

  • Doing Business indicators, 160

  • Double counting problem

    • in CDA, 30–31

    • in MIMIC, 30–31

  • Double shift, 200

  • Drug dealing, 13n4

  • Duopoly markets, 362n6

  • Duval, R., 146

  • Dybka, P. M., 28–30, 47–48, 50

  • Dynamic general equilibrium (DGE), 92, 224

    • for informality measurement, 232

E

  • Ease of Doing Business Index, 133

  • Easterly, W., 122

  • Eberhardt, M., 158

  • Econometric analysis, 91, 164–65, 320, 359

  • Economic development. See also Developing countries

    • benchmark model, 94–95

    • data on, 93, 116

    • empirical methods, 91–92

    • empirical results, 93–105

    • GDP as proxy for, 88n2, 90, 97

    • informal economy and, 6

    • literature on, 90–91

    • policy implications and, 102–5

    • robustness checks, 96–102

    • shadow economy and, 87–88, 90

  • Economy names, 106t, 107t. See also specific topics

  • Education

    • attainment, 89–91, 93, 95, 178, 179, 198, 199, 209, 210, 212

    • demographics of, 200f

    • drop outs, 199

    • financial access linked to, 329

    • in formal sector, 210

    • gender gaps in, 198f

    • immigration and, 184t

    • incomplete, 198

    • informal employment and, 197f, 199, 201f

    • informality linked to, 199, 201f

    • in informal sector, 210

    • marriage and, 199, 202–04

    • in rural areas, 199, 210

    • in Senegal, 192, 198–200, 200f, 201f, 207

    • shadow economy and, 104–05

    • in sub-Saharan Africa, 198f, 201f, 205f

    • in Sustainable Development Goals, 206n12

    • in urban areas, 199, 210–11

    • of women, 197–200, 200f, 201f

  • Ehsaas Kafalat, 298

  • Elbahnasawy, N., 95, 241

  • Electricity consumption, shadow economy measured by, 23–24

  • Electronic payment systems, 80

  • Elgin, C., 49, 91, 92, 94, 224, 230–33, 236

    • on informal economy, 223, 224, 225f, 232f

  • Ellis, M., 95, 233, 241

  • Embaye, A., 49

  • Emerging markets, 71, 76, 78, 146, 148, 157, 159, 167, 224–27, 234, 277, 289, 300, 319, 336

    • gender gap in, 299f

    • immigration impacting, 170, 185

    • taxation in, 254–57

    • VATs in, 229, 254, 255, 258, 271–72

  • Employment. See also Informal employment; Unemployment

    • ILO on, 191n1

    • immigration and, 167–72

    • immigration short term effects on, 174t

    • in informal economy, 167, 191n1

    • of native workers, 172–73, 174n6

    • rates, 159n11, 174, 177–78

    • self-employment, 178, 182t, 183, 183t

    • in Senegal, 192

    • in sub-Saharan Africa, 167

    • wage-employment, 168–69, 174, 174t, 182–83, 182t–84t, 185

  • Employment protection, 150f

    • in South America, 151

  • Employment Protection Legislation Database, 160

  • End-to-end framework, 284–99

  • Enhanced Digital Access Index, 298

  • Entrepreneurship, demographics of, 176f

  • Equality, of women, 206, 209f, 212, 213

  • Equilibrium prices, 365n7

  • Equilibrium wage, 172

  • Erturk, F., 91

  • Esteban-Pretel, J., 146

  • Estonia, 21–23, 30, 48

    • shadow economy in, 30t

  • Ethnic fractionalization, 125, 130

    • factor allocation and, 125

    • in sub-Saharan Africa, 116, 122, 136

  • EU. See European Union

  • Eurobarometer survey, 78n10

  • European System of National and Regional Accounts, 19

  • European Union (EU). See also specific countries

    • corruption in, 76

    • electronic payment system in, 79–80

    • GDP of, 71–73, 76–77

    • human capital development in, 80

    • informality in, 72–73

    • institutional quality in, 78–79

    • labor market reform in, 80

    • output gap estimates in, 75f

    • policy options in, 78–80

    • productivity in, 77–78

    • regulations in, 78–79

    • regulatory quality in, 76, 78

    • remittances in, 77

    • shadow economy determinants in, 76–78

    • shadow economy estimates in, 72–76, 82t–84t

    • shadow economy in, 31f, 71–72

    • shadow economy size in, 73f, 74f, 75t, 76–77, 80

    • taxation in, 76–77, 79–80

  • Exclusion factors, 78, 80

  • Exit factors, 78, 78n9, 78n10, 79

  • Explanatory variables, 27, 72, 128, 326, 327–28, 355

F

  • Factor allocation

    • in Asia, 128, 141f

    • credit access and, 130–32

    • determinants of, 122–25

    • ethnic fractionalization and, 125, 128, 136

    • firm performance and, 125, 128–30, 131t

    • firm size and, 128

    • heterogeneity in effects of, 128–30

    • in Nigeria, 142f

    • spatial distribution of efficiency of, 141f

    • in sub-Saharan Africa, 122–25, 126t, 129t, 131t, 133

    • taxation and, 130–32

  • Factor markets, 116, 121

  • Family planning, 193, 199, 202, 203, 212

  • FATF. See Financial Action Task Force

  • Fee structure, of G2P transfers, 295–96

  • Feige, E. L., 24, 28

  • Feld, L., 27–28

  • Fertility, GDP linked to, 204f

  • Filer, R. K., 49

  • Financial access. See also Financial inclusion; Formal access; Informal access

    • baseline estimates, 329

    • countries in database, 343t, 344t

    • country-level controls, 327

    • decomposition of, 323f

    • definitions, 319–22

    • drivers of, 324–38

    • education linked to, 329

    • explanatory variables, 327–28

    • facets of, 323–24

    • financial sector health and structure, 328

    • financial variables in, 330–36

    • macroprudential policies and, 318–20, 328–30, 332

    • means and standard deviations of variables, 343t

    • monetary policy and, 327–28

    • monetary variables in, 330–36

    • sources of variables, 341t, 342t

    • study results, 329–38

    • in sub-Saharan Africa, 338, 357–58

    • for women, 329

  • Financial Access Index, 341t

  • Financial Access Survey, 317n3

  • Financial Action Task Force (FATF), 281n7, 315, 338

  • Financial corporations, 93, 93n10

  • Financial crisis of 2008-2010, 268

    • in Greece, 229

  • Financial inclusion

    • balance sheets and, 372–76

    • competition and, 358–72

    • data sources, 352–58

    • empirical models, 358–59

    • global, 321f

    • informality and, 8

    • mobile banking and, 317

    • policy for, 317–19

    • in sub-Saharan Africa, 322f, 349–50, 365, 377

  • Financial institutions, G2P transfers and, 286, 288–89, 293

  • Financial market structure, 330–31

  • Financial Soundness Indicators Database, 354t

    • data from, 353

  • Fintech, 285, 289, 292, 297, 300, 301, 353, 377

  • Firm growth

    • in Asia, 117, 118f, 119f

    • in sub-Saharan Africa, 117, 118f

  • Firm performance

    • factor allocation and, 128–30, 129t

    • labor allocation impacting, 131t, 132

    • land allocation impacting, 131t, 132f

    • spatial distribution of, 139–40

    • in sub-Saharan Africa, 139f

  • Firm size

    • in Asia, 139f

    • factor allocation and, 128

    • land markets and, 125–28

    • in Nigeria, 133–34, 135t

    • regulations and, 125–26

    • in sub-Saharan Africa, 139f

  • Fiscal institutions, taxation and, 227–29

  • Fiscal management, 228–29

  • Fiscal policy, informality and, 7–8

  • Fixed-term contracts, 150f, 152f, 160

  • Foreign workers

    • defining, 168, 169

    • offer curve of, 171

    • skillsets of, 168, 169, 171, 172

    • substitutability of, 176, 177n9, 185

  • Formal access, 320, 326, 329, 338

    • drivers of, 324–38

    • explanatory variables, 327–28

    • macroprudential policies and, 328–29

  • Formalization, 3, 5, 81, 115, 116, 126, 132, 227

  • Formal sector

    • education in, 207, 210

    • immigration and, 173f, 181t, 182t

    • self-employment in, 182t

    • in Senegal, 192, 200, 207, 208t

    • in sub-Saharan Africa, 208

  • Freeman, R. B., 146

  • Frey, B. S., 25

G

  • Game-theoretic models, 350, 355

  • Gaps, 157n9, 180, 185

  • Gates Foundation, 290

  • GCash, 292

  • GDP. See Gross domestic product

  • Gender gap

    • in education, 197, 198f, 199, 207

    • in emerging markets, 299f

    • in G2P transfers, 298–99

    • informality and, 196f

    • in informal sector, 193–206

    • in sub-Saharan Africa, 198f

  • Gender inequality, informality and, 2, 5–6, 196f, 213

  • Generalized method of moments (GMM), 224

  • Gerbrandy, J., 270

  • Germany, shadow economy in, 30t

  • Ghana, 139, 168, 169, 171, 176, 179, 288, 295

    • stylized facts for, 187f

  • Gig economy, 88n3

  • Glitz, A., 169

  • Global Competitiveness Index, 102

  • Global economy, analytical categories of, 111t, 112t

  • Global financial crisis, in Greece, 229

  • Global Financial Development Database, data from, 352–53

  • Global Findex Database, 316, 317n3, 319, 327

    • data from, 352–53

  • Global Gender Gap Index, 194

  • Global System for Mobile Communications Association (GSMA), 279n5, 284n12, 290

  • GMM. See Generalized method of moments

  • Goel, R., 230

  • Goldberger, A. S., 25

  • Goldin, C., 104

  • Governance, 76, 78, 133, 223, 227–30, 256, 300

    • as institutional variable, 231

  • Government accountability, 7, 224, 227, 228, 231, 236, 238

    • in institutional quality, 236

  • Government-to-person (G2P) social transfers

    • in advanced economies, 277n3

    • affordability, 297–98

    • agent network coverage in, 292

    • ATMs in, 293

    • basic delivery components for, 279–81

    • beneficiaries, 287–89

    • built-in triggers, 283n9

    • business model elements of, 296–97

    • channels for, 283t

    • CICO networks and, 294–95

    • communication in, 297

    • coverage of, 276f

    • in COVID-19 crisis, 275–76, 283–84

    • cybersecurity in, 300

    • delivery channel mix, 294

    • designing, 288f

    • digital fraud in, 300

    • digital government in, 289–91

    • digital inclusion foundations, 297–99, 310

    • eligibility criteria, 287–88

    • enablers maturity map, 303–10

    • end-to-end framework for, 284–99

    • evolution of, 284–99

    • expansion of, 276

    • fee structure of, 295–96

    • financial institutions and, 293–94

    • gender gap in, 298–99

    • informality and, 277

    • interoperability of, 296

    • KYC requirements, 288

    • limitations of, 299–301

    • liquidity management, 294–95

    • maturity stages of, 286

    • MMOs in, 291–93

    • MNOs in, 291–93, 305t

    • mobile coverage in, 292–93

    • mobile money life cycle in, 295

    • mobile networks for, 292–93

    • open architecture of, 289–90

    • payment acceptance network, 295–96, 308t

    • payment platforms for, 296

    • population reachability for, 280f

    • program features, 296–97

    • quality of service in, 292

    • regulation of, 300–301

    • risk management, 294

    • for social protection systems, 281–84

    • social registry in, 289

    • streamlined controls for, 290–91

    • sustainable, 284f

    • trained personnel, 295

    • user experience of, 288–89

  • G2P. See Government-to-person social transfers

  • GrabPay, 292

  • Gray economy, 11

  • Greece, global financial crisis in, 229

  • Groningen Growth and Development Centre, 115

  • Gross domestic product (GDP)

    • alternative measures of, 103t

    • benchmark model, 94–95

    • boosting, 95

    • correlation of variables, 108t, 109t

    • credit ratio to, 359

    • as economic development proxy, 90

    • of EU, 72–73

    • fertility linked to, 204f

    • long-term determinants of, 96t

    • MIMIC model excluding, 40t

    • noninstitutional variables, 93

    • nonobserved economy as percentage of, 20t

    • per capita determinants, 93

    • robustness checks, 97

    • shadow economy and, 88, 89f, 91, 92, 94–97, 98t, 99t, 100t, 101t, 102f, 103t, 104, 105

    • shadow wages as proportion of, 21t

    • unemployment responsiveness to change in, 160f

  • GSMA. See Global System for Mobile Communications Association

  • Guangzhou, 269

  • Guinea, 41, 47, 139, 197, 206

  • Gyomai, G., 14, 18, 46, 47

H

  • Hanousek, J., 49

  • Hassan, M., 25, 51, 52, 74

  • Hausman test, 99, 134

  • Herrera, C., 199, 202

  • Hidden activities, in SNA discrepancy method, 18

  • Hiring practices, flexibility in, 150

  • Hodrick-Prescott filter, 157n9

  • Household production, in SNA discrepancy method, 18

  • Hsieh, C.-T., 121

  • H-statistic, 350, 355, 357–59, 362, 365, 371

    • data from, 353–55

  • Human capital, 80, 88, 95, 105, 193, 198, 199, 202, 234

    • in EU, 80

    • in shadow economy, 79

  • Human Development Index, 37–38

I

  • IETU. See Impuesto Empresarial a Tasa Única

  • Illegal activities, in SNA discrepancy method, 18–23

  • Illegal production, 18

  • ILO. See International Labour Organization

  • ILOSTAT, 125n6

  • IMF. See International Monetary Fund

  • Immigration. See also Foreign workers

    • data on, 179–80

    • defining, 177

    • education and, 176–77, 185

    • emerging markets impacted by, 170

    • empirical framework, 174–80

    • employment and, 167–71

    • formal sector and, 173f, 181f

    • inflows, 180n11

    • informal sector and, 181t

    • interregional, 181–83, 185

    • intraregional, 168–69, 174, 176–77, 180–83, 185

    • labor markets and, 168, 174n6

    • literature review on, 169–71

    • models of, 178

    • model specifications, 177–79

    • native workers impacted by, 168–70, 172, 173, 174n6, 176, 177, 180–82, 185

    • policy recommendations, 185–88

    • self-employment and, 182, 182t, 183, 183t, 184t

    • in shadow economy, 79, 80

    • shocks from, 170

    • short-term employment effects, 174t

    • skill groups in, 177, 184–85

    • study results on, 180–85

    • stylized facts, 174–76

    • in sub-Saharan Africa, 167, 169, 171, 175f, 179–80

    • supply shock, 177–78

    • from Syria, 170

    • theoretical framework for labor markets and, 171–174

    • to Turkey, 170

    • wage-employment and, 182t, 183t

  • Impuesto Empresarial a Tasa Única (IETU), 258

  • Impulse response function, for commodity price shocks, 164f

  • Income statistics, national expenditure discrepancy with, 23

  • Income tax, in Mexico, 255, 258, 262, 265

  • India, 256, 267, 269, 279, 287–88

  • Informal access, 319–24

    • drivers of, 324–38

    • explanatory variables, 327–28

    • macroprudential policies and, 328–29

  • Informal economy. See also Shadow economy

    • adults in, 365–72

    • composition of, 175f

    • defining, 1

    • economic development and, 6

    • Elgin on, 232f, 247t–49t

    • employment in, 167

    • institutional variables and, 224

    • measures of, 232f

    • Medina on, 232f, 235t, 237t, 242t–45t

    • natural rate of, 241

    • Oztunali on, 232f, 246t–49t

    • Schneider on, 232f, 235t, 237t, 246t–49t

    • size of, 1–3, 4f, 6, 238, 241, 327

    • size of, by income level, 4f

    • size of, by region, 4f

    • social assistance programs and, 278f

    • in sub-Saharan Africa, 195f

    • women in, 191–92, 211–13

  • Informal employment

    • defining, 353

    • education and, 197f

    • ILO on, 353

    • in Senegal, 207–09

    • in sub-Saharan Africa, 353

  • Informality, 1, 5, 6, 148–49

    • as cheating, 257

    • in China, 265–66

    • countercyclical properties of, 157

    • cross-sectional data on, 148n3

    • decreasing, 225, 226f

    • defining, 1

    • DGE for measurement of, 232

    • drivers of, 2

    • education linked to, 201f

    • effective policy design, 4–5

    • in EU, 73

    • financial inclusion and, 8

    • forms of, 1–2

    • GDP transfers and, 277

    • gender gaps and, 197f

    • gender inequality and, 2, 6–7

    • institutions and, 227–231

    • Kanbur on, 1

    • labor markets and, 6–7

    • in Latin America, 148–49

    • marriage and, 202f, 211

    • measuring, 225, 231–32

    • MIMIC models for measurement of, 231–32

    • nonobserved economy classified by, 20t

    • Okun’s coefficients and, 161t

    • productivity and, 6–7

    • root causes of, 5

    • social protection and, 257

    • in sub-Saharan Africa, 194, 194f

    • taxation and, 1, 5, 8, 253–57

    • unemployment and, 156f

  • Informal sector

    • defining, 191n1

    • education in, 210

    • gender gaps in, 193–06

    • IMF on, 193–06

    • immigration and, 181t

    • inspection of, 120

    • institutional quality and, 97n14

    • native workers in, 181–82

    • production, 19

    • self-employment in, 183t

    • in Senegal, 208t

    • in SNA discrepancy method, 19–20

    • in sub-Saharan Africa, 117, 195f

    • taxation and, 97n14

    • wage-employment in, 183t

  • Informal workers

    • contracts of, 2

    • COVID-19 impacting, 3

    • ILO on, 3

    • women, 193–97

  • Infrastructure investment, 255, 267

  • Inspection, labor allocation and, 123

  • Institutional access, for women, 205

  • Institutional quality

    • corruption in, 236

    • in EU, 79–80

    • government accountability in, 236

    • improving, 79–80

    • informal sector and, 97n14

    • measurement of, 236

    • robustness checks for, 236–37

  • Institutional variables

    • business environment as, 229–30

    • corruption as, 231

    • data on, 234

    • governance as, 231

    • informal economy and, 224

    • in political environment, 230–31

    • regime change as, 230–31

    • regulatory burden as, 230

    • study results, 234–38

    • stylized facts on, 224–27

    • taxation and, 228–29

  • Institutions, 230

    • data on, 239t, 240t

    • financial, 293–94

    • fiscal, 228–29

    • informality and, 227–31

    • robustness checks on, 241–49

    • summary statistics on, 239–40

  • Instrumental variables (IV), 116, 128–30

    • in first-stage regression, 130

  • Inter-American Development Bank, 148n3, 153n6

  • International Country Risk Guide, 229

  • International Labour Organization (ILO), 1, 81n13, 118, 148n3, 150, 151, 151n4, 153n6, 160, 191, 353, 370

    • on employment, 191n1

    • on female informal workers, 193–94

    • on informal employment, 353

    • on informal workers, 2

    • on minimum wage, 118–19

    • reports of, 3

  • International Monetary Fund (IMF), 81n13

    • on informal sector, 193

  • Interswitch, 292

  • ISO Codes, 106t, 107t

  • IV. See Instrumental variables

H

  • Jakarta, 272

  • JavaScript, 290

  • Jiménez, G. S., 373

  • Johnson, S., 227, 230

  • Joreskog, K., 25

K

  • Kaliberda, A., 23

  • Kanbur, R., 1, 260

  • Kapetanios, G., 158

  • Karachi, 256, 272

  • Karmann, A., 25

  • Kaufmann, D., 23, 230, 327

  • Keen, M., 259, 260

  • Kelmanson, Ben, 6, 72, 76

  • Keluarga Harapan, 287

  • Kenya, 139, 198, 286, 292–94, 296

  • Khera, P., 146, 162

  • Kigali, 289

  • Kirabaeva, Koralai, 6

  • Kirchgaessner, G., 27, 28

  • Kireyev, A., 270

  • Kiyasseh, Lama, 8

  • Klenow, P., 121

  • Kolmogorov-Smirnov test, 117

  • Kraay, A., 327

  • Krstic, G., 22

  • Kugler, A., 146

  • Kuwait, 100

  • KYC requirements, 288

L

  • Labor allocation

    • efficiency of, 116

    • firm performance impacted by, 132f

    • inspection and, 123

    • in Nigeria, 134f, 142f

    • regulatory quality and, 123

    • state capacity and, 123

    • in sub-Saharan Africa, 124f

  • Labor force, shadow economy and discrepancies in, 23

  • Labor informality

    • business cycle and, 162–64

    • in Latin America, 149f

    • models of, 162–64

    • Okun’s coefficients and, 163

  • Labor institutions, Okun’s coefficients and, 159–62

  • Labor markets

    • immigration and, 168, 172

    • informality and, 6–7

    • institutions, 149–153

    • in Latin America, 145, 149–53, 152f, 164–65

    • low-skilled, 173–74

    • minimum wage and, 120

    • Okun’s coefficient and, 161t

    • reforms in EU, 80

    • regulation of, 115–16, 120

    • rigidity, 150f, 151f, 152f

    • shadow economy and, 103t, 104–05

    • in sub-Saharan Africa, 117, 169

    • theoretical framework for immigration and, 171–74

  • Labor productivity

    • in Central America, 147

    • in Latin America, 147

    • in South America, 147

  • Labor regulations, in sub-Saharan Africa, 127t

  • Lack economy, 11

  • Lambert, Frederic, 7, 162

  • Land allocation

    • in Asia, 122f

    • firm performance impacted by, 132f

    • in Nigeria, 134, 141f, 142f

    • in sub-Saharan Africa, 122, 122f, 141f

  • Land markets

    • in Asia, 119f

    • firm size and, 125–28

    • in sub-Saharan Africa, 117

  • Land ownership, 117, 121, 123, 212

  • Land regulations, in sub-Saharan Africa, 127t

  • La Porta, R., 162

  • LATE. See Local average treatment effect

  • Latin America, 2, 4, 7, 41, 145, 146

    • heterogeneity in, 148

    • informality in, 148–49, 153

    • labor informality in, 149f

    • labor markets in, 149, 152, 152f, 157, 164, 165

    • labor productivity in, 147

    • Okun’s law for, 157–62

    • output informality in, 149f

    • shadow economy in, 41–45

    • unemployment in, 149, 153–57, 154f, 156f

  • Latvia, 21–23, 48

  • Legal barriers

    • in Senegal, 208–09

    • for working women, 204–06

  • Leigh, D., 159

  • Lerner index, 350, 355, 357–59, 362, 371

    • data from, 356

  • Levine, R., 122

  • Levy, S., 257, 259, 261, 262, 271

  • Lewis, W. A., 169, 170

  • Leyva, Angelica Martínez, 7, 146

  • Lichard, T., 49

  • Light density, 231n2

  • Light intensity approach, 12, 12n3, 34, 51

  • Liquidity management, in G2P transfers, 294–95

  • Lithuania, 22, 23, 48

  • Lithuanian Free Market Institute, 21

  • Loayza, N., 227, 234

  • Local average treatment effect (LATE), 128

  • Logit regressions

    • with baseline controls, 333t

    • multinomial, 330t, 332f, 334t, 335t

  • Loungani, P., 146, 159

M

  • MacDonald, Margaux, 8

  • Macedonia, 73

  • Macroprudential policies, 316, 318–20, 328–29

    • demand-side, 332, 336

    • financial access and, 328–29, 338–39

    • formal access and, 329–30

    • informal access and, 329–30

    • leaks in, 336

    • loose, 336–38

    • regional controls on, 329

    • supply-side, 332

    • survey, 316, 328

    • tight, 336–38

  • Malaysia, 139, 170, 292

  • Malta, Vivian, 7

  • Mansoor, A., 270

  • Maquiladora system, 261, 262

  • MAR. See Missing at random

  • Markets. See specific topics

  • Marriage, 202, 206

    • education and, 192, 197, 199, 203, 204, 208, 211

    • informality and, 202, 202f, 203f, 211

  • Marshall, Alfred, 256

  • Martinez Peria, M. S., 318

  • Mastruzzi, M., 327

  • Mauritius, 139, 193, 202, 206, 267

  • MCAR. See Missing completely at random

  • Medina, Leandro, 6, 74, 232, 233, 327

    • on informal economy, 225f, 232f, 235t, 237t, 242t–45t

    • MIMIC model used by, 90, 92, 224

    • on shadow economy, 94–95

  • Mengistu, Azanaw, 8, 318, 331

  • Mertens, J., 171

  • Mexican Tax Administration, 258, 260, 262

  • Mexico, 148, 153, 155, 157, 254–56, 262, 263

    • income tax in, 258

    • Maquiladora system in, 261–62, 261f

    • property taxes in, 272

    • social protection in, 257, 266

    • tax evasion in, 259–62

    • tax reforms in, 257–63

    • VATs in, 257–63, 265–66

  • Meza-Cuadra, C., 227, 234

  • Miami, 170

  • Middle East, 205, 329

  • Migration. See Immigration

  • MIMIC. See Multiple indicators, multiple causes model

  • Minimum wage, 117–20, 126–27, 151f, 152f, 153

    • ILO on, 117–18

    • labor markets and, 117–18

    • productivity and, 118–19

    • in sub-Saharan Africa, 117–19

  • Minnesota Population Center, 176

  • Mintz, J., 259

  • Missing at random (MAR), 36

  • Missing completely at random (MCAR), 36

  • Missing not at random (MNAR), 36

  • MMOs. See Mobile money operators

  • MNAR. See Missing not at random

  • MNOs. See Mobile network operators

  • Mobile banking, financial inclusion and, 317

  • Mobile money life cycle, 295

  • Mobile money operators (MMOs), 285, 290, 291, 305t

    • in G2P transfers, 284f, 285f, 288f, 291–93

  • Mobile network operators (MNOs), 281, 285, 291

    • in G2P transfers, 285, 291, 292, 294, 306t

    • in Nigeria, 285n13

  • Mobile wallets, 285, 291, 294, 296

  • Mojaloop, 290

  • Monetary policy, financial access and, 327–28

  • Monetary transaction approach, to shadow economy, 24

  • Monras, J., 170

  • Montenegro, C. E., 25

  • Montoro, C., 146

  • Moonlighting, 14n5

  • Morales Acevedo, A., 355

  • M-Pesa, 286, 292

  • Multinomial logit regressions

    • with baseline controls, 330t, 334t, 335t, 337t

    • margin plots of, 332f

  • Multiple indicators, multiple causes (MIMIC) model, 6, 12, 72, 224

    • absolute values in, 26

    • adjusted, 47t, 48

    • for advanced economies, 36t, 41t

    • calibration of, 12n2

    • components of, 28

    • for developing countries, 35t, 40t

    • double counting problem in, 30–31, 51

    • estimation procedure, 25f, 26, 28, 48

    • estimation results, 31–45, 32t–36t, 40t, 41t, 51–52

    • GDP excluded from, 41t

    • identification problem with, 27–28

    • for informality measurement, 231–32

    • macro, 25–31

    • measurement model, 28–30

    • Medina using, 6, 224

    • negative variance in, 28–29

    • of OECD countries, 25, 45, 47t

    • PMM in, 38–41

    • results, 41–50

    • reverse standardization, 28

    • robustness tests, 38–41, 51

    • Schneider using, 6, 34, 47–49, 51–52

    • for shadow economy, 12, 26–27, 65f

    • for shadow economy in EU, 75t, 83t–84t

    • shortcomings of, 34–41

    • SNA discrepancy method and, 45–48

    • structural model, 28

    • structured hybrid model-based estimation, 14, 28–30

    • for sub-Saharan Africa, 48t

    • using night lights, 34, 35t, 36t

  • Mumbai, 272

  • Munkacsi, Z., 146, 162

  • Myanmar, 139, 292

N

  • Namibia, 139, 283n10

  • National expenditure, income statistics discrepancy with, 23

  • National Statistical Offices, 18

  • Native workers

    • defining, 168

    • employment of, 177–78

    • immigration impacting, 168, 177–78

    • in informal sector, 181–82

    • skillsets of, 172–73

    • substitutability of, 177n9

  • Natural rate, of informal economy activity, 241

  • Necessity-driven self-employment, 183

  • Nelson, M., 230

  • Niger, 37, 133, 281

  • Nigeria, 121, 132–35, 193, 281

    • demographics of, 133

    • factor allocation in, 141f

    • firm size in, 135t

    • labor allocation in, 142f

    • land allocation in, 142f

    • MNOs in, 285n13, 292, 300

    • population of, 133

    • poverty in, 133

    • taxation in, 133, 134f

  • Night lights

    • for MIMIC model, 35t, 36t, 66f, 231

    • for shadow economy estimation, 34–36

  • Nonobserved economy

    • categories in, 18–20

    • classification of, 19, 19f

    • by GDP, 20

    • by informality type, 20t

  • Nose, Manabu, 6, 7

  • Novissi, 281, 297

  • Nunhuck, Soheib, 8

O

  • OECD. See Organization for Economic Co-operation and Development

  • Official economy, shadow economy and development of, 17t, 24

  • Official labor force, actual labor force discrepancy with, 23

  • Oil-exporting countries, robustness tests for, 99–101

  • Okun’s coefficient

    • absolute value of, 163

    • informality and, 161t

    • labor informality and, 163f

    • labor institutions and, 159–62

    • labor markets and, 161t

  • Okun’s law, 146

    • for Latin America, 157–62

  • Olley, S., 120, 121, 136

  • OLS models, 130, 134

  • Ongena, S., 355

  • Open architecture

    • for G2P transfers, 288–89

    • standards for, 289–90

  • Oportunidades, 254, 258, 259, 263, 263n2

  • Organization for Economic Co-operation and Development (OECD), 18, 20, 25, 41, 45, 150, 151, 151n4, 153

    • MIMIC model of, 47t

    • SNA discrepancy method of, 47t

  • Ottaviano, G. G., 170

  • Output gap, 74n4

    • estimates of, in EU, 75f

  • Output informality, in Latin America, 149f

  • Ozden, C., 170

  • Oztunali, O., 49, 92, 94, 224, 233, 236

    • on informal economy, 232f, 246t, 247t

P

  • Pakes, A., 120, 121, 136

  • Pakistan, 254, 258, 259, 266, 271, 279, 293, 298

  • Panel regression, 92, 96, 99, 133

    • with one-period lags, 101t

    • with two-period lags, 101t

  • Paraguay, 292

  • Patrinos, H., 198

  • Payment acceptance network, for G2P transfers, 295–96, 308t

  • Payment platforms, for G2P transfers, 296

  • Payments, 18, 24, 79–81, 117, 123, 231, 281, 286, 288–97, 310, 324, 349, 353, 377

  • Payroll tax, 5, 119, 120, 162, 253–55, 257, 258

  • Peña Nieto, Enrique, 259

  • Perez-Saiz, Hector, 8, 318, 331

  • Peri, G. G., 170

  • Peru, 147, 148, 153, 155, 157, 281, 289, 295

  • Pesaran, M. H., 158

  • Pescatori, A., 162

  • Philippines, 139, 279n4

  • Pischke, J., 169

  • PMM. See Predictive mean matching

  • Poland, 20–22, 48

  • Policy. See also Macroprudential policies

    • economic development and, 104–05

    • in EU, 79–80

    • for financial inclusion, 317–19

    • immigration, 167, 185

    • of shadow economy and implications for, 102–05

    • for sub-Saharan Africa, 136

    • for women in informal sector, 211–13

  • Political environment, institutional variables in, 230–31

  • Polity IV Database, 228n1

  • Population

    • in COVID-19 crisis needing support, 277f

    • of Nigeria, 133

    • of sub-Saharan Africa, 115–16

  • Poverty, in Nigeria, 133

  • PPP. See Purchasing power parity

  • Prady, Delphine, 8

  • Predictive mean matching (PMM), 12, 36–38, 52

    • advantages of, 37, 38

    • in MIMIC model, 36–38

    • for shadow economy estimation, 39t

    • similarity principle for, 37

  • Presbitero, A. F., 158

  • Probit regressions, 214t–20t

  • Procyclical effects, 351

  • Productivity

    • in Asia, 140f

    • in EU, 76–77

    • informality and, 6–7

    • minimum wage and, 118–19

    • shadow economy and, 76–78

    • in sub-Saharan Africa, 117, 140f

    • total factor, 91

  • Propensity score matching, 37

  • Property rights, for women, 205

  • Property taxes

    • in China, 268

    • in Mexico, 267

    • occupancy-based, 270

    • public services linked to, 268–70

    • for SDGs, 256–57

  • Psacharopoulos, G., 198

  • Public services

    • property taxes linked to, 268–70

    • shadow economy and, 15t–16t

  • Public Use Microdata Samples (PUMS), 174

  • Purchasing power parity (PPP), 93

  • Putnins, T., 22, 48

Q

  • Qatar, 100

  • Qin, D., 318

R

  • Random effects logit, 236, 237t, 244t, 245t, 248t

  • Real income, consumption linked to, 172

  • Real output total factor productivity (TFPQ), 121

  • Rebei, N., 319

  • Redistributionist policies, 254

  • Redundancy costs, 7, 151f, 152, 152f, 153, 160

  • Reforms, tax, 254, 255

    • in Mexico, 257–263

  • Refugees

    • shadow economy and, 45n29

    • Syrian, 170–71

  • Regime change, as institutional variable, 230–31

  • Régimen de Incorporación Fiscal (RIF), 262

  • Regressions

    • IV in first-stage, 130

    • logit, 333t

    • multinomial logit, 326, 330t, 332f, 334t, 335t, 337t

    • panel, 92, 96, 99, 100t, 101t, 133

    • in robustness test, 92

  • Regulations. See also specific topics

    • in EU, 79–80

    • firm size and, 125–28

    • of G2P transfers, 300–01

    • improving, 78–79

    • of labor markets, 115–16, 120

    • shadow economy and, 15t–17t

    • in sub-Saharan Africa, 117

  • Regulatory barriers, 79

  • Regulatory burden, 223, 227–28, 230

  • Regulatory quality

    • in EU, 76

    • labor allocation and, 123

    • shadow economy and, 76

    • in sub-Saharan Africa, 124f

  • Reilly, B., 22

  • Remittances, in EU, 77

  • REPECOS, 257, 258, 260, 261, 262, 271

  • Representative surveys, in SNA discrepancy method, 20–22

  • Reproductive health care, in sub-Saharan Africa, 199, 205, 205f

  • Responsibility System, 263, 264

  • Restrepo-Echavarria, P., 146

  • Reverse standardization, 28

  • Ribadu Committee Report, 266

  • RIF. See Régimen de Incorporación Fiscal

  • Risk management, in G2P transfers, 294

  • Rivera-Batiz, F., 168, 171, 172

  • Robinson, J., 227

  • Robustness checks

    • dummy variables in, 92

    • economic development, 96–102

    • GDP, 96–102

    • for institutional quality, 236

    • on institutions, 241

    • for MIMIC model, 38–41

    • for oil-exporting countries, 99–102

    • regressions in, 93

    • for taxation, 97

    • with 5-year averages, 98–99

    • with 10-year averages, 96, 98

  • Rubin, D. B., 12, 52

  • Ruge, M., 50

  • Rukumnuaykit, P., 170

  • Rural areas

    • education in, 199, 200f

    • in Senegal, 199, 200f

  • Rwanda, 171, 206, 289, 296

S

  • Safaricom, 292

  • Sahay, R., 318

  • Sahn, D. E., 199

  • SAS Proc MI procedure, 38

  • Sauka, A., 22, 48

  • Savings, 281, 318, 323, 324f, 326, 335, 336, 338

  • Saxegaard, M., 146, 162

  • Schneider, Friedrich, 6, 25, 27, 34, 47, 48, 232

    • on electronic payment systems, 80

    • on informal economy, 223, 224, 225f, 232f, 233, 235t, 237t, 242t–45t, 248t, 249t, 278f, 327

    • MIMIC model used by, 49–51, 90, 224

    • on shadow economy, 72, 92, 94

  • Schoar, A., 183

  • Schoeni, R. F., 169

  • SDGs. See Sustainable Development Goals

  • Self-employment, 30, 37, 169

    • in formal sector, 182t

    • immigration and, 174, 182, 183

    • in informal sector, 172, 183t

    • necessity-driven, 183

    • transformational, 183

  • SEM. See Structural equation modeling

  • Senegal, 206–11

    • context of, 206–09

    • education in, 198–200, 200f, 201f, 207

    • empirical analysis of, 209–11

    • employment in, 192

    • family code in, 208

    • formal sector in, 199–200

    • informal employment in, 197f

    • informal sector in, 192

    • legal barriers in, 208–09

    • microdata from, 192

    • rural areas in, 199, 200f, 208t

    • social norms in, 207–08

    • urban areas in, 199, 201f, 208t

    • women in, 200, 205–06, 209f

    • World Bank on, 208

  • SEZs. See Special economic zones

  • Shadow economy

    • in Baltic countries, 22t

    • in Caribbean, 41–42

    • causation of, 12–13

    • CDA for, 12, 23, 26, 30t

    • in CIS, 73–75

    • company manager surveys and, 22–23

    • correlation of variables, 108t, 109t

    • corruption and, 15t, 76

    • countercyclical nature of, 73–74

    • during COVID-19, 81

    • defining, 11–12, 14n9, 52

    • determinants of, in EU, 78–79

    • deterrence and, 16t

    • direct estimation approaches, 49–50

    • direct estimation methods, 14–23

    • economic development and, 87–88, 91

    • education and, 105

    • electricity consumption for measurement of, 23–24

    • estimates of, in EU, 72–76, 75f

    • in Estonia, 30t

    • in EU, 31f

    • Feld on, 27–28

    • GDP and, 87, 88, 89f, 90–97, 94t, 98t–101t, 102f, 103t, 104, 105

    • as GDP proportion, 21t

    • in Germany, 30t

    • human capital in, 77

    • indirect estimation approaches, 23–25, 51–52

    • labor market implications, 104–05

    • in Latin America, 41

    • long-term trends in, 90

    • Medina on, 25, 94

    • migration in, 77

    • MIMIC model for, 12, 24–25, 65f

    • MIMIC model for, in EU, 75t, 82t–84t

    • monetary transaction approach to, 24

    • names for, 11

    • night lights for estimation of, 34–36

    • official economy development and, 17t

    • PMM for estimation of, 39t

    • policy implications, 102–05

    • productivity and, 77–78

    • public sector services and, 16t

    • refugees and, 45n29

    • by region, 45f

    • regulations and, 15t

    • regulatory quality and, 78

    • Schneider on, 27, 90, 92, 94

    • size of, 46f, 53t–64t

    • size of, in EU, 73f, 74f

    • social security and, 15t

    • statistical office estimates of, 29, 29t

    • in sub-Saharan Africa, 41

    • summary statistics of, 42t, 43t, 44t

    • taxation and, 15t, 16t, 76–77, 79–80

    • theoretical considerations, 13–14

    • trade openness and, 76

  • Shanghai, 267, 268

  • Shenzhen, 265

  • Shleifer, A., 162, 234

  • Skill groups

    • in immigration, 170, 184–85

    • low-skilled, 172–74

  • Skillsets

    • of foreign workers, 167–69

    • of native workers, 167–70

  • Slovak Republic, 20, 46, 49, 73, 74

  • SNA. See System of National Accounts

  • SNA discrepancy method

    • defining, 14n9

    • hidden activities in, 18

    • household production in, 18

    • illegal activities in, 18–20

    • illegal production in, 18

    • informal sector production in, 18

    • MIMIC model and, 45–48

    • of OECD countries, 47t

    • representative surveys in, 20–22

    • statistical underground in, 18

    • for sub-Saharan Africa, 48t

    • for underground hidden production, 14

  • Social assistance programs

    • informal economy and, 278f

    • taxonomy of, 279

  • Social norms, 213

    • women and, 200–04

  • Social protection, 2, 5, 191, 211, 254, 256, 275–77, 302

    • G2P for, 281–84

    • informality and, 257

    • in Mexico, 267

  • Social registry, in G2P transfers, 289

  • Social security, shadow economy and, 15t

  • South Africa, 139, 168, 169, 171, 176, 179, 180, 202, 267

    • stylized facts for, 188f

  • South America. See also specific countries

    • employment protection in

    • labor productivity in

  • Sparreboom, T., 171

  • Spearman’s rank correlation, 38

  • Special economic zones (SEZs), 254

  • Stakeholders, 284, 287, 294n16, 297, 300, 310

  • State capacity, 123

    • defining, 123

    • labor allocation and, 123

  • Statistical offices, shadow economy estimates from, 29t

  • Statistical underground, in SNA discrepancy method, 18

  • Structural equation modeling (SEM), 25

  • Structural reforms, in China, 263–66

  • Subnational services, taxation for, 267–71

  • Sub-Saharan Africa, 6–8, 47, 136. See also specific countries

    • aggregate-level analysis of, 121–32

    • agriculture in, 117

    • capital ratios in, 374n8

    • competition in, 358–72

    • COVID-19 in, 167–68

    • credit access in, 130–32

    • data on, 120–21

    • deindustrialization of, 115

    • demographics in, 117

    • education in, 198f, 199

    • empirical analysis of, 121–34

    • employment in, 167–69

    • ethnic fractionalization in, 116, 122

    • factor allocation in, 121, 126t, 131t, 141f

    • factor misallocations in, 121–22

    • financial access in, 357–58

    • financial inclusion in, 321f, 349

    • firm growth in, 118f, 136

    • firm performance in, 128–30, 129t, 131t, 132f, 139f

    • firm size in, 117, 119f, 121, 128

    • formal sector in, 195f, 338

    • gender gaps in, 193–06, 195f

    • immigration in, 167–69, 173f, 179–80

    • informal economy in, 195f

    • informal employment in, 353

    • informality in, 116, 194, 194f

    • informal sector in, 115, 195f

    • labor allocation in, 122, 124f, 132f

    • labor markets in, 117, 169

    • labor regulations in, 127t

    • land allocation in, 122, 122f, 132f

    • land markets in, 117

    • land regulations in, 127t

    • MIMIC models for, 47, 47t, 48t

    • minimum wage in, 117–19

    • policy recommendations for, 136

    • population of, 115

    • productivity in, 117, 140f

    • regulations in, 117

    • regulatory quality in, 124f

    • reproductive health care in, 199, 205f

    • shadow economy in, 41

    • SNA discrepancy method for, 48t

    • summary statistics for, 137t–38t

    • taxation in, 130–32

    • theoretical framework for analysis of, 119–20

    • women in, 200–06, 209f

  • Summary statistics

    • for Asia, 137t, 138t

    • on institutions, 238

    • of shadow economy, 42t, 43t, 44t

    • for sub-Saharan Africa, 137t, 138t

    • of variables, 110t, 239t, 240t

  • Supply-loan instruments, 328n8

  • Supply-side macroprudential policies, 332

  • Sustainable Development Goals (SDGs), 255

    • China and, 272

    • on education, 206n12

    • property taxes for, 256–57

    • taxation for, 255–56

  • Sweden, 21, 22, 29

  • Syria

    • immigration from, 170

    • refugees from, 170–71

  • System of National Accounts (SNA), 12

    • discrepancy method, 47t, 48t

  • Systems GMM estimations, 234–36

T

  • Takaful program, 289

  • Tanzania, 292

  • Tanzi, V., 24

  • Tavares, Marina M., 7

  • Taxation. See also Value added taxes

    • area-based, 270

    • in emerging markets, 254–55

    • in EU, 76, 79–80

    • evasion of, in Mexico, 259–62

    • factor allocation and, 130–32

    • fiscal institutions and, 228–29

    • income, 259

    • informality and, 1, 5, 8, 253–57

    • informal sector and, 97n14

    • institutional variables and, 228–29

    • national reforms to, 254–55

    • in Nigeria, 133, 134f

    • payroll, 119–20

    • reforms in Mexico, 257–263

    • reforms to, in China, 263–66

    • robustness check for, 97

    • for SDGs, 255–56

    • shadow economy and, 15t, 16t, 72, 76–77

    • for subnational service provision, 267–71

    • in sub-Saharan Africa, 128

    • tax-benefit links at government levels, 270–71

    • in United Kingdom, 267

  • Testaverde, M., 170

  • TFP. See Total factor productivity

  • TFPQ. See Real output total factor productivity

  • Thatcher, Margaret, 256, 268

  • Tigo, 292

  • Togo, 139, 279, 281, 297

  • Toscani, Frederik, 7, 162

  • Total factor productivity (TFP), 91, 121, 162

  • Tourpe, Herve, 8

  • Trade openness, 6, 32, 36, 51, 74, 76, 93, 125, 128, 231

  • Transfers, 3, 5, 80, 117, 212, 254, 255, 257–59, 268, 269, 271, 275, 276, 279, 281, 283, 284, 286, 287, 292, 293

  • Transformational self-employment, 183

  • Transparency, 79, 81, 105, 133, 261, 302, 315

  • Transparency International Corruption Perceptions Index, 133

  • Tumen, S., 170

  • Turkey, immigration to, 170

U

  • Undeclared working hours, 21t, 22

  • Underground hidden production, in SNA discrepancy method, 14–18

  • Unemployment, 30, 31, 34–35, 51, 71, 145, 146, 149, 155–60, 171, 277

    • cyclical sensitivity of, 159n12

    • GDP changes and, 160f

    • informality and, 156f, 163

    • in Latin America, 153–57

  • United Arab Emirates, 100

  • United Kingdom, 29, 73n3, 256, 267, 268, 270

    • taxation in, 267

  • United Nations Sustainable Development Goals, 2

  • United States, 41, 169, 170, 256, 267

  • Unstructured supplementary service data (USSD), 286n14, 291

  • Urban areas

    • education in, 199, 201f

    • in Senegal, 199, 201f, 208t

  • User experience, of G2P social transfers, 288–89

  • USSD. See Unstructured supplementary service data

V

  • Value added taxes (VATs)

    • in China, 265

    • in emerging markets, 254–55

    • in Mexico, 257–60

  • van de Ven, P., 14, 18, 46–48

  • VATs. See Value added taxes

  • Velling, J., 169

  • Villa, K., 202

  • Violence, towards women, 208–09

  • Viseth, Arina, 7, 176

W

  • Wage determination, flexibility in, 150f

  • Wage-employment

    • in formal sector, 182t

    • immigration and, 182t, 183t

    • in informal sector, 183t

  • Wave Money, 292

  • WDI. See World Development Indicators

  • Weck-Hanneman, H., 25

  • WGI. See Worldwide Governance Index

  • Wieladek, T., 318

  • Winter-Ebmer, R., 169

  • Wodon, Q., 200–02

  • Women. See also Gender gap

    • competitiveness of, 200–04

    • credit access for, 206

    • discrimination against, 213

    • double shift of, 200–02

    • education of, 197–200

    • equality of, 206, 209f, 212

    • financial access for, 329

    • in informal economy, 193–94, 210–11

    • informal workers, 193–94

    • institutional access for, 205

    • legal barriers for working, 204–06

    • policy recommendations for, 211–13

    • property rights for, 205

    • in Senegal, 206–11, 209f

    • social norms and, 200–04

    • in sub-Saharan Africa, 209f

    • violence towards, 208–09

  • Women and Men in the Informal Economy, 3

  • Working hours, undeclared, 21t

  • World Bank, 92n8, 93, 95, 97, 130, 152n5, 208, 270

    • on Senegal, 208

  • World Bank Employment Protection Legislation, 151

  • World Bank Enterprise Survey, 95, 116, 120, 120n3, 123, 123n4, 133

    • balance sheets from, 117

  • World Development Indicators (WDI), 93, 158

  • World Economic Forum, 102, 149, 151, 194

  • World Economic Outlook, 97, 158

  • Worldwide Governance Index (WGI), 92n8, 93, 95

  • Wright, G., 170

  • Wu, Dong Frank, 6

X

  • Xiaoping, Deng, 263

  • Xu, Rui, 8

Y

  • Yamagata, T., 158

Z

  • Zhang, X., 318

  • Zhong, X., 318

  • Zhuravskaya, E., 122

  • Zoido-Lobaton, P., 230

  • Z-tests, 216t–20t

  • Zukauskas, V., 48

  • Zweimüller, J., 169

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