Conceptualising and evaluating inclusive economic development: a productivity perspective

Figures & data

Table 1. Methods for measuring inclusive economic growth.

Method	Content	Source
Equity index	The weighted average of growth in average income. Changes in the index reflect income distribution.	Aoyagi and Ganelli (2015), Anand et al. (2013), Alekhina and Ganelli (2021)
Theil index	An index that is calculated by aggregating the ratio of the share of income of each state to its population, reflecting the inequality among regions within a country.	Barua and Sawhney (2015)
GDP growth generated by social inclusion processes	The effects of the development of social inclusion in particular aspects (gender, financial inclusion, democracy, etc.) on economic growth, based on the theory that social inclusion brings about economic growth, but economic growth does not necessarily bring about social inclusion.	Cabeza-García at al. (2018), Cabeza-García at al. (2019)
Income of low-income people	The average income of the lowest 20% quantile.	Dollar and Kraay (2002), Dollar, Kleineberg, and Kraay (2016), Kang and Martinez-Vazquez (2021)
Income of most wealthy people	The income share of the top 1% quantile.	Bassier and Woolard (2021)
Principal component analysis (PCA)	Compute the principal components based on high-dimension data consisting of various indicators related to inclusive growth, including income, wealth accumulation, infrastructure, education, health, and unemployment.	Whajah, Bokpin, and Kuttu (2019)
Social opportunity function	Distribution of accessibility to a particular category of service.	Ali and Son (2007), Mitra (2017)
Multidimensional indicator system	Five indicators according to five criteria of inclusive economic growth: (1) growth in the employment rate, (2) wage growth relative to GDP growth; (3) wage growth in sectors with initially low wages; (4) employment growth in high-wage sectors; (5) structural transformation.	Kjøller-Hansen and Sperling (2020)
Weighted indicator system	Construct indicator systems based on the definition or theory of inclusive economic growth with weights that are pre-defined or calculated by the entropy weight method (EWM). Indicators change according to research perspectives but usually include GDP per capita, Gini index, education, infrastructure, and employment.	McKinley (2010), Khan et al. (2016), Sun, Liu, and Tang (2018), Sharafutdinov et al. (2019), Jiang et al. (2021)

Figure 1. Evaluation framework. References: Whiteford (2017), Li et al. (2021), Johnstone (2022).

Table 2. Data definition and sources.

Category		Variable	Definition	Source
Input	Capital	cap	Capital stock (constant 2017 US Dollar, in millions).	Penn World Table (Feenstra, Inklaar, and Timmer 2015)
	Labor	labor	Employed population (in millions).	World Development Indicators (World Bank 2021)
	Energy	energy	Primary energy consumption (terawatt-hours).	Energy, Our World in Data (Ritchie and Roser 2020)
Desired output	GDP	gdp	Real GDP (constant 2017 US Dollar, in millions).	Penn World Table (Feenstra, Inklaar, and Timmer 2015)
	Schooling year	edu	Average years of schooling based on Barro and Lee (2013).
	Democracy	demo	Total value index of democracy matrix, scale 0–1.	Democracy Matrix (Lauth and Oliver 2021)
	Governance	gov	World governance indicator, on average of 6 sub-indicators.	World Governance Indicator (Kaufmann, Kraay, and Mastruzzi 2011)
Undesired output	Child mortality	mortal	Child mortality under 5 years old per 1000 live births.	World Development Indicators (World Bank 2021)
	PM2.5 Exposure	pm25	Mean annual exposure of the population to PM2.5 air pollution (micrograms per cubic meter).
	Gini index	gini	Standardised reported Gini index.	World Income Inequality Database (UNU-WIDER 2021)

Table 3. Summary statistics of the data.

Variable	Obs	Mean	SD	Min	Max
Panel A: Full sample
cap	1599	4539.48	9923.72	30.66	101703.02
labor	1599	24.47	88.18	0.15	799.31
energy	1599	1473.88	4329.34	8.96	39360.93
gdp	1599	986.41	2541.23	7.22	20566.03
edu	1599	2.91	0.51	1.54	4.35
demo	1599	0.75	0.22	0.06	0.98
gov	1599	0.41	0.88	−1.33	1.97
mortal	1599	17.18	19.99	2.00	146.90
pm25	1599	16.84	10.22	2.91	86.61
gini	1599	38.93	9.48	22.42	74.23
Panel B: Developed countries
cap	693	6363.65	11273.00	30.66	69059.06
labor	693	14.31	26.91	0.15	158.30
energy	693	1792.63	4414.17	18.53	26943.48
gdp	693	1326.54	2967.08	8.76	20566.03
edu	693	3.27	0.34	2.23	4.35
demo	693	0.90	0.08	0.33	0.98
gov	693	1.25	0.45	−0.74	1.97
mortal	693	4.68	1.65	2.00	15.90
pm25	693	13.28	5.67	2.91	53.75
gini	693	32.51	4.85	22.42	50.74
Panel C: Developing countries
cap	906	3144.16	8498.40	31.91	101703.02
labor	906	32.24	114.18	0.15	799.31
energy	906	1230.07	4249.63	8.96	39360.93
gdp	906	726.25	2124.85	7.22	20118.08
edu	906	2.64	0.45	1.54	3.62
demo	906	0.63	0.22	0.06	0.95
gov	906	−0.24	0.51	−1.33	1.29
mortal	906	26.75	22.18	4.40	146.90
pm25	906	19.57	11.94	3.09	86.61
gini	906	43.84	9.22	25.31	74.23

Table 4. Summary statistics of the iTFP estimation results.

	Mean	SD	Min	Max
Full sample	0.69	0.30	0.00	1.19
Developed countries	0.90	0.17	0.04	1.19
Developing countries	0.53	0.29	0.00	1.09

Figure 2. Mapping results of the iTFP indexes.

Notes: The map is colored based on the TFP index in 2019. Source: Author’s calculations.

Table 5. Summary statistics of the iTFP estimation results, categorized by region.

	2000	2005	2010	2015	2019
Americas
Caribbean	0.29	0.31	0.30	0.30	0.32
Central America	0.47	0.62	0.49	0.45	0.47
Northern America	0.91	0.92	0.96	0.95	0.98
Southern America	0.40	0.45	0.60	0.49	0.34
Asia
Central Asia	0.40	0.42	0.45	0.44	0.59
Eastern Asia	0.71	0.76	0.78	0.74	0.70
South-eastern Asia	0.65	0.66	0.69	0.70	0.57
Southern Asia	0.79	0.80	0.72	0.67	0.66
Western Asia	0.68	0.56	0.67	0.66	0.51
Europe
Eastern Europe	0.60	0.64	0.68	0.66	0.75
Northern Europe	0.85	0.92	0.94	0.97	1.00
Southern Europe	0.72	0.74	0.70	0.66	0.69
Western Europe	0.68	0.56	0.67	0.66	0.51
Oceania
Australia and New Zealand	0.87	0.86	0.95	0.88	0.89

Notes: Region and sub-region classification is based on the World Bank's standard. Africa is excluded from the table due to low data availability.

Aoyagi, Chie, and Giovanni Ganelli. 2015. “Asia’s Quest for Inclusive Growth Revisited.” Journal of Asian Economics 40 (October): 29–46. doi:10.1016/j.asieco.2015.06.005

 Google Scholar

Anand, Rahul, Saurabh Mishra, Shanaka J. Peiris, and Paul Cashin. 2013. “Inclusive Growth: Measurement and Determinants.” IMF Working Papers 2013 (135): 3–15.

 Google Scholar

Alekhina, Victoriia, and Giovanni Ganelli. 2021. “Determinants of Inclusive Growth in ASEAN.” Journal of the Asia Pacific Economy (December): 1–33. doi:10.1080/13547860.2021.1981044

 Google Scholar

Barua, Alokesh, and Aparna Sawhney. 2015. “Development Policy Implications for Growth and Regional Inequality in a Small Open Economy: The Indian Case.” Review of Development Economics 19 (3): 695–709. doi:10.1111/rode.12154.

 Web of Science ®Google Scholar

Dollar, David, and Aart Kraay. 2002. “Growth Is Good for the Poor.” Journal of Economic Growth 7 (3): 195–225. doi:10.1023/A:1020139631000

 Web of Science ®Google Scholar

Dollar, David, Tatjana Kleineberg, and Aart Kraay. 2016. “Growth Still Is Good for the Poor.” European Economic Review 81 (January): 68–85. doi:10.1016/j.euroecorev.2015.05.008.

 Google Scholar

Kang, Hyojung, and Jorge Martinez-Vazquez. 2021. “When Does Foreign Direct Investment Lead to Inclusive Growth?” The World Economy December: twec.13236.

 Google Scholar

Bassier, Ihsaan, and Ingrid Woolard. 2021. “Exclusive Growth? Rapidly Increasing Top Incomes Amid Low National Growth in South Africa.” South African Journal of Economics 89 (2): 246–273. doi:10.1111/saje.12274

 Web of Science ®Google Scholar

Whajah, Jennifer, Godfred A. Bokpin, and Saint Kuttu. 2019. “Government Size, Public Debt and Inclusive Growth in Africa.” Research in International Business and Finance 49 (October): 225–240. doi:10.1016/j.ribaf.2019.03.008

 Google Scholar

Ali, Ifzal, and Hyun Hwa Son. 2007. “Measuring Inclusive Growth.” Asian Development Review, Asian Development Review 24 (1): 11–31.

 Google Scholar

Mitra, Siddhartha. 2017. “A Note on Measuring Inclusive Growth and the Inclusiveness of Growth.” South Asian Journal of Macroeconomics and Public Finance 6 (2): 194–208. doi:10.1177/2277978717727168

 Google Scholar

Kjøller-Hansen, Anders Oskar, and Lena Lindbjerg Sperling. 2020. “Measuring Inclusive Growth Experiences: Five Criteria for Productive Employment.” Review of Development Economics 24 (4): 1413–1429. doi:10.1111/rode.12689

 Web of Science ®Google Scholar

McKinley, Terry. 2010. “Inclusive Growth Criteria and Indicators: An Inclusive Growth Index for Diagnosis of Country Progress.” Sustainable Development Working Papers, no. 14 (June). https://www.adb.org/publications/inclusive-growth-criteria-and-indicators-inclusive-growth-index-diagnosis-country.

 Google Scholar

Khan, Azra, Gulzar Khan, Sadia Safdar, Sehar Munir, and Zubaria Andleeb. 2016. “Measurement and Determinants of Inclusive Growth: A Case Study OfPakistan (1990-2012).” The Pakistan Development Review 55 (4): 455–466. doi:10.30541/v55i4I-IIpp.455-466.

 Google Scholar

Sun, Caizhi, Ling Liu, and Yanting Tang. 2018. “Measuring the Inclusive Growth of China’s Coastal Regions.” Sustainability 10 (8): 2863. doi:10.3390/su10082863

 Web of Science ®Google Scholar

Sharafutdinov, Rustam Ilfarovich, Elvir Munirovich Akhmetshin, Aleksandra Grigorievna Polyakova, Vladislav Olegovych Gerasimov, Raisa Nikolaevna Shpakova, and Mariya Vladimirovna Mikhailova. 2019. “Inclusive Growth: A Dataset on Key and Institutional Foundations for Inclusive Development of Russian Regions.” Data in Brief 23 (April): 103864.

 PubMedGoogle Scholar

Jiang, Aichun, Chuan Chen, Yibin Ao, and Wenmei Zhou. 2021. “Measuring the Inclusive Growth of Rural Areas in China.” Applied Economics May: 1–14.

 Google Scholar

Whiteford, Gail. 2017. “Participation in Higher Education as Social Inclusion: An Occupational Perspective.” Journal of Occupational Science 24 (1): 54–63. doi:10.1080/14427591.2017.1284151

 Web of Science ®Google Scholar

Li, Zhihui, Xinyan Zhou, Shuyao Ran, and Fernando C Wehrmeister. 2021. “Social Protection and the Level and Inequality of Child Mortality in 101 Low- and Middle-Income Countries: A Statistical Modelling Analysis.” Journal of Global Health 11 (04067): 1–11.

 Google Scholar

Johnstone, Christopher J. 2022. “Conceptualising Inclusive Development by Identifying Universality, Plurality, Sociality, and Relationality.” Journal of International Development January: jid.3622.

 Google Scholar

Feenstra, Robert C., Robert Inklaar, and Marcel P. Timmer. 2015. “The Next Generation of the Penn World Table.” American Economic Review 105 (10): 3150–3182. doi:10.1257/aer.20130954

 Web of Science ®Google Scholar

World Bank. 2021. World Development Indicators. Washington, D.C: World Bank.

 Google Scholar

Ritchie, Hannah, and Max Roser. 2020. “Energy.” Our World in Data. November 28, 2020. https://ourworldindata.org/energy.

 Google Scholar

Barro, Robert J., and Jong Wha Lee. 2013. “A New Data Set of Educational Attainment in the World, 1950–2010.” Journal of Development Economics 104 (September): 184–198. doi:10.1016/j.jdeveco.2012.10.001

 Web of Science ®Google Scholar

Lauth, Hans-Joachim, and Schlenkrick Oliver. 2021. Democracy Matrix Codebook. Würzburg: Julius-Maximilians-Universität Würzburg. www.democracymatrix.com.

 Google Scholar

Kaufmann, Daniel, Aart Kraay, and Massimo Mastruzzi. 2011. “The Worldwide Governance Indicators: Methodology and Analytical Issues.” Hague Journal on the Rule of Law 3 (2): 220–246. doi:10.1017/S1876404511200046

 Web of Science ®Google Scholar

UNU-WIDER. 2021. World Income Inequality Database (WIID). Version 31 May 2021.

 Google Scholar