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Licensed Unlicensed Requires Authentication Published by De Gruyter March 26, 2021

Rethinking Unconditional Convergence in Manufacturing in the Age of New Technologies

  • Bilge Erten EMAIL logo and Oliver Schwank

Abstract

We revisit unconditional convergence within manufacturing with a focus on differences in technology intensity across industries. For Latin American and Sub-Saharan African economies, we observe that low-technology and medium-technology intensive industries experience a significantly slower convergence in comparison to high-technology intensive ones. In contrast, we find no evidence of a significant differential for low-technology industries’ convergence in Asian economies, and if anything, we see that medium-technology intensive sectors experience a faster convergence than high-technology industries. In developed economies, we observe that while low-technology industries experience a slightly slower convergence, medium-technology industries converge at similar rates to high-technology industries. We also find that these differences emerge during the period of increased global integration, which exposed developing economies to increased competition both from advanced markets and fast industrializers within the developing world. Finally, we show that differential convergence patterns are stronger after the peak of manufacturing employment share has been reached. We discuss the implications of these trends for the future of development policy making.


Corresponding author: Bilge Erten, Department of Economics, Northeastern University, 43 Leon Street, 312A Lake Hall, Boston, MA 02115, USA, E-mail:

Appendix: Additional tables

Table A1:

List of countries and time period.

Country Time period Country Time period
Algeria 1972–2017 Kuwait 1967–2017
Argentina 1963–2002 Latvia 1986–2016
Australia 1963–2017 Libya 1964–1980
Austria 1963–2017 Luxembourg 1985–2017
Bangladesh 1967–2011 Madagascar 1967–2006
Barbados 1970–1997 Malawi 1964–2012
Belgium 1963–2017 Malaysia 1968–2017
Bolivia 1970–2014 Malta 1963–2017
Brazil 1963–2017 Mauritius 1968–2017
Canada 1963–2017 Mexico 1984–2017
Central African Republic 1973–1993 Mongolia 1990–2017
Chile 1963–2017 Morocco 1976–2015
China 1977–2017 Netherlands 1963–2017
China, Hong Kong SAR 1973–2008 New Zealand 1963–2017
China, Macao SAR 1978–2016 Nicaragua 1963–1985
Colombia 1963–2017 Nigeria 1963–1996
Costa Rica 1963–2017 Norway 1963–2017
Cyprus 1963–2017 Occupied Palestinian Territory 1994–2017
Czech Republic 1987–2017 Oman 1993–2017
Czechoslovakia 1963–1991 Pakistan 1963–2006
Denmark 1963–2017 Panama 1963–2017
Dominican Republic 1963–2016 Papua New Guinea 1963–2001
Ecuador 1963–2017 Peru 1974–2017
Egypt 1964–2017 Philippines 1963–2017
El Salvador 1963–1998 Poland 1963–2017
Eritrea 1992–2016 Portugal 1963–2017
Ethiopia 1990–2015 Republic of Korea 1963–2017
Ethiopia and Eritrea 1965–1989 Romania 1963–2017
Fiji 1968–2016 Russian Federation 1993–2017
Finland 1963–2017 Senegal 1974–2014
France 1963–2017 Singapore 1963–2017
Germany, Fed. Rep 1963–1990 Slovakia 1991–2017
Germany 1991–2017 Slovenia 1987–2017
Ghana 1963–2003 South Africa 1963–2017
Greece 1963–2017 Spain 1963–2017
Guatemala 1968–2006 Swaziland 1967–2014
Honduras 1963–1996 Sweden 1963–2017
Hungary 1963–2017 Syrian Arab Republic 1963–2010
Iceland 1967–2017 Taiwan 1973–2017
India 1963–2017 Macedonia 1987–2017
Indonesia 1970–2017 Trinidad and Tobago 1966–2006
Iran 1963–2017 Tunisia 1963–2017
Iraq 1963–2017 Turkey 1963–2017
Ireland 1963–2017 United Kingdom 1963–2017
Israel 1963–2017 United Republic of Tanzania 1965–2017
Italy 1967–2017 United States of America 1963–2017
Jamaica 1963–2006 Uruguay 1968–2014
Japan 1963–2017 Venezuela 1963–1998
Jordan 1963–2017 Yugoslavia 1963–1989
Kenya 1963–2017 Zambia 1963–2015
  1. The table provides the list of countries in our sample together with the time coverage for each country, including the beginning and end dates of data.

Table A2:

Time period and number of countries.

Time period Number of countries
1965–1975 83
1975–1985 89
1985–1995 100
1995–2005 93
2005–2015 85
  1. This table provides the number of countries we have data on key indicators for the different time periods.

Table A3:

Robustness check using a common sample.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.020*** −0.057*** −0.041*** −0.065*** −0.012* −0.044*** −0.083*** −0.098*** −0.090** −0.130***
(0.005) (0.007) (0.007) (0.011) (0.006) (0.007) (0.020) (0.018) (0.025) (0.025)
Base × low-technology intensive 0.005 0.005 0.023** 0.020*** 0.002 0.003 0.047* 0.048* 0.049 0.069**
(0.004) (0.004) (0.009) (0.007) (0.007) (0.008) (0.021) (0.024) (0.027) (0.023)
Base × medium-technology intensive −0.003 −0.005 0.008 0.004 −0.005 −0.004 0.024 0.026 0.017 0.040
(0.004) (0.003) (0.009) (0.005) (0.007) (0.005) (0.015) (0.015) (0.029) (0.022)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 62 62 22 22 14 14 10 10 7 7
Number of observations 3813 3813 1679 1679 873 873 445 445 265 265
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A4:

Robustness check excluding observations with the lowest 10% values for growth.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.024*** −0.050*** −0.036*** −0.054*** −0.012* −0.041*** −0.045*** −0.066*** −0.086** −0.103***
(0.004) (0.005) (0.005) (0.008) (0.007) (0.007) (0.012) (0.009) (0.031) (0.021)
Base × low-technology intensive 0.007* 0.007** 0.016** 0.015** 0.002 0.003 0.014 0.017* 0.055* 0.059**
(0.004) (0.003) (0.006) (0.006) (0.008) (0.007) (0.011) (0.009) (0.027) (0.020)
Base × medium-technology intensive −0.003 −0.002 0.005 0.003 −0.013 −0.008 0.002 0.008 0.061** 0.056***
(0.004) (0.004) (0.006) (0.004) (0.009) (0.008) (0.011) (0.010) (0.025) (0.018)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 100 100 26 26 18 18 20 20 14 14
Number of observations 4355 4355 1689 1689 882 882 634 634 303 303
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A5:

Robustness check excluding observations with the highest 10% values for growth

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.011*** −0.043*** −0.025*** −0.040*** −0.001 −0.029*** −0.066** −0.093*** −0.026 −0.064*
(0.003) (0.004) (0.004) (0.006) (0.003) (0.004) (0.027) (0.024) (0.035) (0.032)
Base × low-technology intensive 0.001 0.001 0.008** 0.004 −0.004 −0.001 0.046* 0.047* 0.010 0.015
(0.003) (0.003) (0.003) (0.004) (0.003) (0.005) (0.024) (0.023) (0.030) (0.028)
Base × medium-technology intensive −0.001 −0.003 0.001 −0.004 −0.007*** −0.006* 0.038 0.040* −0.005 0.009
(0.003) (0.002) (0.003) (0.003) (0.002) (0.003) (0.023) (0.023) (0.034) (0.034)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 100 100 26 26 18 18 20 20 14 14
Number of observations 4486 4486 1683 1683 867 867 674 674 367 367
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A6:

Robustness check excluding former socialist countries.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.021*** −0.061*** −0.043*** −0.060*** −0.011* −0.048*** −0.074*** −0.104*** −0.087*** −0.114***
(0.004) (0.006) (0.010) (0.012) (0.006) (0.007) (0.024) (0.020) (0.015) (0.016)
Base × low-technology intensive 0.005 0.004 0.018 0.016* −0.003 −0.001 0.049** 0.049** 0.050*** 0.045***
(0.004) (0.004) (0.011) (0.009) (0.007) (0.007) (0.020) (0.019) (0.011) (0.015)
Base × medium-technology intensive −0.004 −0.005 0.004 0.002 −0.018* −0.011* 0.032 0.036* 0.039** 0.038**
(0.004) (0.003) (0.011) (0.008) (0.009) (0.006) (0.020) (0.019) (0.013) (0.015)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 95 95 23 23 17 17 20 20 14 14
Number of observations 4675 4675 1643 1643 960 960 738 738 413 413
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A7:

Robustness check excluding OECD countries.

All Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8)
Log initial productivity −0.042*** −0.073*** −0.010 −0.048*** −0.074*** −0.104*** −0.087*** −0.114***
(0.008) (0.008) (0.012) (0.010) (0.024) (0.020) (0.015) (0.016)
Base × low-technology intensive 0.015** 0.013** −0.007 −0.001 0.049** 0.049** 0.050*** 0.045***
(0.007) (0.006) (0.012) (0.012) (0.020) (0.019) (0.011) (0.015)
Base × medium-technology intensive 0.005 0.006 −0.028** −0.014 0.032 0.036* 0.039** 0.038**
(0.007) (0.006) (0.011) (0.010) (0.020) (0.019) (0.013) (0.015)
Country fixed effects No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 75 75 14 14 20 20 14 14
Number of observations 3116 3116 705 705 738 738 413 413
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A8:

Robustness check excluding industry controls.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.017*** −0.032*** −0.021*** −0.025*** −0.017** −0.029*** −0.015*** −0.019*** −0.037*** −0.043**
(0.002) (0.003) (0.003) (0.004) (0.006) (0.005) (0.005) (0.004) (0.011) (0.016)
Base × low-technology intensive 0.000 0.000* −0.000 −0.000 0.000 0.001 0.001 0.001 0.001 0.001
(0.000) (0.000) (0.000) (0.000) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Base × medium-technology intensive 0.001*** 0.002*** 0.000* 0.001** 0.001 0.002** 0.002** 0.003*** 0.003** 0.003*
(0.000) (0.000) (0.000) (0.000) (0.001) (0.001) (0.001) (0.001) (0.001) (0.002)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects No No No No No No No No No No
Period fixed effects No No No No No No No No No No
Number of countries 100 100 26 26 18 18 20 20 14 14
Number of observations 4904 4904 1808 1808 985 985 738 738 413 413
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A9:

Robustness check using log of value added as weights.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.024*** −0.061*** −0.039*** −0.060*** −0.013* −0.049*** −0.067*** −0.096*** −0.084*** −0.111***
(0.004) (0.005) (0.005) (0.009) (0.006) (0.007) (0.019) (0.015) (0.015) (0.015)
Base × low-technology intensive 0.007* 0.005 0.017** 0.014** −0.001 0.001 0.042*** 0.041*** 0.047*** 0.043***
(0.003) (0.003) (0.007) (0.006) (0.007) (0.007) (0.014) (0.014) (0.011) (0.014)
Base × medium-technology intensive −0.002 −0.003 0.006 0.003 −0.015* −0.009* 0.024 0.029* 0.037** 0.037**
(0.004) (0.003) (0.006) (0.004) (0.008) (0.005) (0.015) (0.015) (0.013) (0.014)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 100 100 26 26 18 18 20 20 14 14
Number of observations 4904 4904 1808 1808 985 985 738 738 413 413
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A10:

Robustness check using growth rates calculated from log-linear trend using 10 annual observations.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.019*** −0.052*** −0.029*** −0.047*** −0.004 −0.039*** −0.066*** −0.094*** −0.098*** −0.110***
(0.004) (0.005) (0.003) (0.008) (0.003) (0.007) (0.021) (0.015) (0.016) (0.017)
Base × low-technology intensive 0.004 0.003 0.010** 0.007* −0.008 −0.005 0.044** 0.044*** 0.067*** 0.056***
(0.004) (0.003) (0.004) (0.003) (0.005) (0.006) (0.017) (0.015) (0.013) (0.017)
Base × medium-technology intensive −0.005 −0.006 0.001 −0.002 −0.026** −0.019** 0.030* 0.036** 0.055*** 0.046**
(0.005) (0.004) (0.003) (0.003) (0.011) (0.008) (0.017) (0.015) (0.015) (0.017)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 100 100 26 26 18 18 20 20 14 14
Number of observations 4904 4904 1808 1808 985 985 738 738 413 413
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A11:

Robustness check focusing on region-specific differential effects in a fully interacted specification with full sample.

All
(1) (2)
Base × developed −0.004** −0.046***
(0.002) (0.008)
Base × Asia −0.003 −0.027***
(0.002) (0.009)
Base × Latin America −0.007*** −0.054***
(0.002) (0.006)
Base × Sub-Saharan Africa −0.009*** −0.070***
(0.002) (0.009)
Base × other −0.006*** −0.061***
(0.002) (0.007)
Base × developed × low-technology intensive −0.000 0.001
(0.001) (0.001)
Base × Asia × low-technology intensive 0.001 0.002*
(0.001) (0.001)
Base × Latin America × low-technology intensive 0.001 0.003**
(0.001) (0.001)
Base × Sub-Saharan Africa × low-technology intensive 0.001 0.002
(0.002) (0.002)
Base × other × low-technology intensive 0.001 0.002
(0.001) (0.001)
Base × developed × medium-technology intensive −0.001 −0.000
(0.001) (0.001)
Base × Asia × medium-technology intensive −0.000 0.001**
(0.001) (0.001)
Base × Latin America × medium-technology intensive 0.000 0.003**
(0.002) (0.001)
Base × Sub-Saharan Africa × medium-technology intensive 0.000 0.004**
(0.002) (0.001)
Base × other × medium-technology intensive 0.001 0.002*
(0.002) (0.001)
Country fixed effects No Yes
Industry fixed effects Yes Yes
Period fixed effects Yes Yes
Period × industry fixed effects Yes Yes
Number of countries 100 100
Number of observations 4904 4904
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A12:

Robustness check using an alternative time period split, 1965–1995.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.013** −0.052*** −0.022** −0.037*** 0.011* −0.030*** −0.079** −0.112*** −0.063* −0.079***
(0.006) (0.006) (0.009) (0.012) (0.005) (0.006) (0.033) (0.026) (0.032) (0.024)
Base × low-technology intensive 0.005 0.005 0.006* 0.005 −0.004 −0.003 0.058* 0.054** 0.043 0.042
(0.005) (0.005) (0.003) (0.005) (0.007) (0.009) (0.029) (0.025) (0.027) (0.026)
Base × medium-technology intensive −0.006 −0.006 −0.008 −0.007 −0.016* −0.017* 0.043 0.047* 0.033 0.028
(0.005) (0.005) (0.005) (0.005) (0.009) (0.008) (0.029) (0.025) (0.031) (0.026)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 86 86 23 23 17 17 19 19 12 12
Number of observations 2893 2893 968 968 604 604 575 575 273 273
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A13:

Robustness check using an alternative time period split, 1995–2015.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.033*** −0.064*** −0.046*** −0.064*** −0.029*** −0.054*** −0.062*** −0.081*** −0.114*** −0.121***
(0.006) (0.007) (0.008) (0.014) (0.009) (0.017) (0.015) (0.007) (0.026) (0.007)
Base × low-technology intensive 0.008* 0.005 0.021** 0.016* 0.001 −0.001 0.023** 0.035** 0.052*** 0.047*
(0.005) (0.004) (0.010) (0.008) (0.009) (0.008) (0.008) (0.010) (0.012) (0.022)
Base × medium-technology intensive 0.001 −0.002 0.012 0.006 −0.012 −0.008 −0.020 −0.009 0.053** 0.052***
(0.006) (0.005) (0.008) (0.006) (0.010) (0.006) (0.017) (0.019) (0.016) (0.012)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 66 66 25 25 14 14 6 6 6 6
Number of observations 2011 2011 840 840 381 381 163 163 140 140
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A14:

Heterogeneity within low-technology intensive products.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.025*** −0.063*** −0.038*** −0.061*** −0.011* −0.049*** −0.074*** −0.105*** −0.087*** −0.115***
(0.004) (0.005) (0.005) (0.009) (0.006) (0.007) (0.024) (0.020) (0.015) (0.016)
Base × textiles, clothing, footwear 0.010** 0.005 0.014** 0.010* −0.008 −0.008 0.045** 0.045** 0.049* 0.034
(0.004) (0.004) (0.007) (0.005) (0.007) (0.005) (0.020) (0.018) (0.023) (0.024)
Base × food, beverages, tobacco 0.006 0.011* 0.027*** 0.028*** 0.005 0.013 0.062*** 0.068*** 0.054*** 0.064***
(0.005) (0.006) (0.007) (0.007) (0.008) (0.011) (0.020) (0.020) (0.015) (0.020)
Base × wood, paper, recycling 0.007* 0.003 0.010 0.004 −0.006 −0.007 0.041* 0.035* 0.044** 0.030*
(0.004) (0.003) (0.007) (0.005) (0.006) (0.006) (0.021) (0.019) (0.016) (0.016)
Base × medium-technology intensive −0.002 −0.003 0.005 0.002 −0.018* −0.011* 0.032 0.036* 0.039** 0.038**
(0.004) (0.003) (0.006) (0.004) (0.008) (0.006) (0.020) (0.019) (0.013) (0.015)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 100 100 26 26 18 18 20 20 14 14
Number of observations 4904 4904 1808 1808 985 985 738 738 413 413
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

Table A15:

Heterogeneity within low-technology intensive products.

All Developed Asia Latin America Sub-Saharan Africa
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Log initial productivity −0.025*** −0.063*** −0.038*** −0.060*** −0.011* −0.048*** −0.074*** −0.105*** −0.087*** −0.113***
(0.004) (0.005) (0.005) (0.009) (0.006) (0.007) (0.024) (0.020) (0.015) (0.016)
Base × low-technology intensive 0.007** 0.006 0.017** 0.014** −0.003 −0.001 0.049** 0.049** 0.050*** 0.045***
(0.004) (0.003) (0.007) (0.006) (0.007) (0.007) (0.020) (0.019) (0.011) (0.015)
Base × petroleum, chemicals, plastics −0.001 0.001 0.003 −0.000 −0.023** −0.012 0.042* 0.046* 0.048*** 0.047***
(0.006) (0.004) (0.007) (0.005) (0.010) (0.007) (0.023) (0.023) (0.012) (0.015)
Base × iron, steel, metal products −0.001 −0.006 0.010 0.005 −0.017* −0.014** 0.029 0.034 0.024 0.026*
(0.004) (0.004) (0.008) (0.005) (0.009) (0.006) (0.025) (0.023) (0.013) (0.014)
Base × machinery and equipment −0.001 −0.004 0.007 0.004 −0.010 −0.004 0.004 0.006 0.062*** 0.045**
(0.004) (0.004) (0.005) (0.004) (0.007) (0.006) (0.022) (0.018) (0.019) (0.019)
Base × transport equipment −0.006 −0.009 0.005 0.002 0.001 −0.010 0.030 0.037* 0.021 0.028
(0.007) (0.006) (0.006) (0.005) (0.012) (0.009) (0.022) (0.020) (0.031) (0.031)
Country fixed effects No Yes No Yes No Yes No Yes No Yes
Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Period × industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Number of countries 100 100 26 26 18 18 20 20 14 14
Number of observations 4904 4904 1808 1808 985 985 738 738 413 413
  1. The table presents evidence on unconditional convergence using regression results from Eq. (1). Robust standard errors are clustered at the country level. ***, **, * denote significance at the 1, 5, and 10% levels, respectively.

References

Amsden, A. H., and T. Hikino. 1993. “Borrowing Technology or Innovating: An Exploration of the Two Paths to Industrial Development.” In Learning and Technological Change, 243–66. London: Palgrave Macmillan.10.1007/978-1-349-22855-3_13Search in Google Scholar

Barro, R. J., X. S. i Martin, O. J. Blanchard, and R. E. Hall. 1991. “Convergence across States and Regions,” In Brookings Papers on Economic Activity, 107–82.10.2307/2534639Search in Google Scholar

Bates, R. H., J. H. Coatsworth, and J. G. Williamson. 2007. “Lost Decades: Postindependence Performance in Latin America and Africa,” The Journal of Economic History 917–43, https://doi.org/10.1017/s0022050707000447.Search in Google Scholar

Baumol, W. J. 1986. “Productivity Growth, Convergence, and Welfare: What the Long-Run Data Show,” The American Economic Review 1072–85.Search in Google Scholar

Belli, P. 1991. “Globalizing the Rest of the World.” Harvard Business Review 69 (4): 50–5.Search in Google Scholar

Dasgupta, S., and A. Singh. 2006. Manufacturing, Services and Premature Deindustrialization in Developing Countries: A Kaldorian Analysis, Research Paper, UNU-WIDER. United Nations University (UNU).10.1057/9780230801462_23Search in Google Scholar

De Long, J. B. 1988. “Productivity Growth, Convergence, and Welfare: Comment.” The American Economic Review 78 (5): 1138–54.Search in Google Scholar

De Souza, J. P. A. 2017. “Real Wages and Labor-Saving Technical Change: Evidence from a Panel of Manufacturing Industries in Mature and Labor-Surplus Economies.” International Review of Applied Economics 31 (2): 151–72, https://doi.org/10.1080/02692171.2016.1225017.Search in Google Scholar

Felipe, J., A. Mehta, and C. Rhee. 2019. “Manufacturing Matters but It’s the Jobs that Count.” Cambridge Journal of Economics 43 (1): 139–68.10.1093/cje/bex086Search in Google Scholar

Frey, C. B., and M. A. Osborne. 2017. “The Future of Employment: How Susceptible are Jobs to Computerisation?” Technological Forecasting and Social Change 114: 254–80, https://doi.org/10.1016/j.techfore.2016.08.019.Search in Google Scholar

Galindo-Rueda, F., and F. Verger. 2016. OECD Taxonomy of Economic Activities Based on R&D Intensity. OECD iLibrary.Search in Google Scholar

Haraguchi, N., C. F. C. Cheng, and E. Smeets. 2017. “The Importance of Manufacturing in Economic Development: Has this Changed?” World Development 93: 293–315. https://doi.org/10.1016/j.worlddev.2016.12.013.Search in Google Scholar

Harrison, A. 2019. “International Trade or Technology? Who is Left Behind and What to do About it.” Journal of Globalization and Development 9 (2): 1–15.10.1515/jgd-2018-0027Search in Google Scholar

Harrison, A., and A. Rodríguez-Clare. 2010. “Trade, Foreign Investment, and Industrial Policy for Developing Countries,” In Handbook of Development Economics, Vol. 5, 4039–214. Elsevier.10.3386/w15261Search in Google Scholar

International Monetary Fund. 2019. The Future of Work in Sub-Saharan Africa. Washington, DC: International Monetary Fund.Search in Google Scholar

Kaldor, N. 1966. Causes of the Slow Rate of Economic Growth of the United Kingdom: An Inaugural Lecture. London: Cambridge University Press.Search in Google Scholar

Kinfemichael, B., and A. K. M. Morshed. 2019. “Unconditional Convergence of Labor Productivity in the Service Sector.” Journal of Macroeconomics 59: 217–29, https://doi.org/10.1016/j.jmacro.2018.12.005.Search in Google Scholar

Lall, S. 1992. “Technological Capabilities and Industrialization.” World Development 20 (2): 165–86, https://doi.org/10.1016/0305-750x(92)90097-f.Search in Google Scholar

Lawrence, R. Z., and L. Edwards. 2013. “US Employment Deindustrialization: Insights from History and the International Experience.” Policy Brief: 13–27.Search in Google Scholar

Maddison, A. 2009. Statistics on World Population, GDP and Per Capita GDP. Available at http://www.ggdc.net/maddison/oriindex.htm.Search in Google Scholar

Madsen, J. B., and I. Timol. 2011. “Long-Run Convergence in Manufacturing and Innovation-Based Models.” Review of Economics and Statistics 93 (4): 1155–71, https://doi.org/10.1162/rest_a_00147.Search in Google Scholar

Mankiw, N. G., D. Romer, and D. N. Weil. 1992. “A Contribution to the Empirics of Economic Growth.” Quarterly Journal of Economics 107 (2): 407–37, https://doi.org/10.2307/2118477.Search in Google Scholar

Palma, J. G. 2008. “De-Industrialization, ‘Premature’ De-Industrialization and the Dutch Disease.” The New Palgrave Dictionary of Economics 1–8: 1297–306.10.1057/9780230226203.0369Search in Google Scholar

Rodrik, D. 2012. “Unconditional Convergence in Manufacturing.” The Quarterly Journal of Economics 128 (1): 165–204, https://doi.org/10.1093/qje/qjs047.Search in Google Scholar

Rodrik, D. 2016. “Premature Deindustrialization.” Journal of Economic Growth 21 (1): 1–33, https://doi.org/10.1007/s10887-015-9122-3.Search in Google Scholar

Rodrik, D. 2018. “New Technologies, Global Value Chains, and the Developing Economies.” Pathways for Prosperity Commission Background Paper Series; no. 1.10.3386/w25164Search in Google Scholar

Rowthorn, B., and J. R. Wells. 1987. De-industrialization and Foreign Trade. CUP Archive. Cambridge [Cambridgeshire]. New York: Cambridge University Press.Search in Google Scholar

Singh, A. 1977. “UK Industry and the World Economy: A Case of De-industrialization?” In Welfare Aspects of Industrial Markets, 183–214. Boston, MA: Springer.10.1007/978-1-4613-4231-1_10Search in Google Scholar

Tregenna, F. 2011. “Manufacturing Productivity, Deindustrialization, and Reindustrialization,” Technical Report. Working Paper//World Institute for Development Economics Research.Search in Google Scholar

Timmer, M. P., de Vries Gaaitzen, and de Vries Klaas. 2014. Patterns of Structural Change in Developing Countries, 149. Groningen Growth and Development Center Research Memorandum.Search in Google Scholar

Tregenna, F. 2009. “Characterising Deindustrialisation: An Analysis of Changes in Manufacturing Employment and Output Internationally.” Cambridge Journal of Economics 33 (3): 433–66, https://doi.org/10.1093/cje/ben032.Search in Google Scholar

UNIDO. 2017. INDSTAT2. Industrial Statistics Database.Search in Google Scholar

United Nations. 2018. Frontier Technologies for Sustainable Development. New York, NY: World Economic and Social Survey.Search in Google Scholar

World Bank. 2019. World Development Report 2019: The Changing Nature of Work. Washington, DC: World Bank.Search in Google Scholar

Received: 2020-04-20
Accepted: 2021-03-09
Published Online: 2021-03-26

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