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Is there a path to inclusive and low carbon growth? Clovis Freire MPDD UNESCAP The challenges to achieve The future we want • "Poverty eradication is the greatest global challenge facing the world today and an indispensable requirement for sustainable development. In this regard, we are committed to freeing humanity from poverty and hunger as a matter of urgency." • "We reaffirm that climate change is one of the greatest challenges of our time, and we express profound alarm that emissions of greenhouse gases continue to rise globally." (General Assembly resolution 66/288 The future we want, 11 September 2012) Higher income is associated with higher CO2 emissions per capita CO2 emissions (metric tons per capita) 100 10 1 y = 0.0011x0.902 R² = 0.7857 0.1 0.01 100 1,000 10,000 GDP per capita (US$) Source: Author based on data from World Bank, 2011b (accessed November 2011). 100,000 Conceptual framework • Technological and organisational innovations are the engine of economic growth (Schumpeter) • Rapid catching up associated with radical structural transformation of the economy towards activities with higher productivity and higher levels of technological sophistication (Kuznets, 1979; Amsden, 2001; Rodrik) • Carbon emissions as a function of the technology used in the production (life cycle analysis) Conceptual framework (Based on evolutionary growth models ‐ Pasinetti, 1987, 1993; Silverberg and Vespagen, 2005; Metcalfe et al., 2006) Technologies economic activities x1 x2 employment e1 + e2 + productivity output q1 < q2 < q3 y1 + + e 0 = unemployed y2 x3 e3 … y3 xn … + en … < qn … + yn = L = Y Inclusive growth Economic growth with shift share of employment from low to more productive economic activities (productive employment) Technologies economic activities x1 x2 employment e1 + e2 + productivity output q1 < q2 < q3 y1 + + e 0 = unemployed y2 x3 e3 … y3 xn … Xn+1 = n+1 L = L + e + en … < qn < qn+1 … + yn = Yn+1 = Y + y (Diversification) Creation of new and more productive economic activities, which would increase the opportunity for more productive jobs Technologies Energy CO2 economic activities x1 x2 employment e1 + e2 + productivity output q1 < q2 < q3 y1 + y2 + c1 + c2 + Carbon footprint e 0 = unemployed x3 xn … Xn+1 = n+1 L = L + e + en … < qn y3 … + yn = n+1 Y = Y + y c3 … + cn = n+1 Y = C + c e3 … < qn+1 CO2 emissions as a function of the structure of the network of technologies and the sources of energy Carbon footprint cj = (CO2j /ej) Technologies Energy CO2 economic activities x1 x2 employment e1 + e2 + productivity output q1 < q2 < q3 y1 + y2 + c1 + c2 + Carbon footprint e 0 = unemployed x3 xn … Xn+1 1. Foster new economic activities that, in addition of being more productive, emit less carbon = n+1 L = L + e + en … < qn y3 … + yn = n+1 Y = Y + y c3 … + cn = n+1 Y = C + c e3 … Two ways that an economy can evolve through a greener path < qn+1 2. Increase share of renewable energy sources, which require new technologies and therefore new products How diversification would come about? • Path dependency – New activities tend to exploit the technologies that were previously developed for other activities • Innovation – New to the world – Emulation: new to the country • Most frequent form of innovation in developing countries Productive Technologies capacities products x1 x2 x3 productivity q1 < q2 < q3 employment e1 + e2 + output y1 + y2 + e0 = unemployed xn Xn+1 < qn < qn+1 e3 + en =+ en+1 = L L y3 + yn =+ yn+1 = Y Y … Is there a path to inclusive and low carbon growth? • An optimum path of diversification of economic activities may exist, consisting of the continuous move to low‐carbon and more‐productive activities that are closely related to the existing productive capacities of the economy Empirical questions 1) Which economic activities are more likely to emerge given the existing technologies in the economy? 2) Which of those have higher productivity? 3) Which of those are greener? 1) Which economic activities are more likely to emerge given the existing technologies in the economy? • Technological trajectory – Evolutionary path of technological development in response to change in industrial development (Nelson and Winter, 1982; Dosi, 1982) – Korean experience: Mature ‐> Consolidation ‐> Emergence (Kim and Dahlman, 1991) • Path dependency – Evolutionary process is strongly path dependent (Nelson, 1995) • Empirical evidence of association between sectors: – Hidalgo, Klinger, Barabási, Hausmann (2007). The Product Space Conditions the Development of Nations – Network: products are nodes connected to each other if they are usually part of the same product mix – proximity between products A and B (ΦAB) – ΦAB = ΦBA = min(P(RCA(A)|RCA(B)), P(RCA(B)|RCA(A))) Source: Hidalgo, C.A., and others (2007) Empirical questions 1) Which economic activities are more likely to emerge given the existing technologies in the economy? – Method of proximity (Product Space), revised (RCA not used), cut‐off<80%, trade data disaggregated by unit code and price range 2) Which of those have higher productivity? 3) Which of those are greener? 2) Which economic activities have higher productivity? • Productivity data – STAN (OECD), INDSTAT (UNIDO), PADI (ECLAC) (Lavopa, 2011) – Limitations: number of countries and disaggregation by sector (28 sectors) • Higher productivity associated with higher levels of technological sophistication – Kuznets, 1979; Chenery, et al., 1986; Amsden, 2001 • Lin (2012) – Six‐step procedure to identify and facilitate growth – “identify the list of tradable goods and services that have been produced for about 20 years in dynamically growing countries with similar endowment structures and a per capita income that is about 100% higher than their own.” Method of reflections Hidalgo and Hausmann (2009). The building blocks of economic complexity. Source: Hidalgo and Hausmann (2009) Product complexity Measure of how ubiquitous the product is and the level of diversification of the countries that produce it 0 2 4 6 8 Maldives 6 4 2 0 Percent 8 Bangladesh 0 2 4 6 8 Japan -4 -2 0 Product complexity (global average=0, sd=1) Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). 2 Economic complexity is associated with higher output The specification relates to the regression (3) presented in the table Empirical questions 1) Which economic activities are more likely to emerge given the existing technologies in the economy? – Method of proximity (Product Space), revised (RCA not used), cut‐off<85%, trade data disaggregated by unit code and price range 2) Which of those have higher productivity? – Method of reflections, revised (RCA not used), cut‐ off<country’s average 3) Which of those are greener? Method – create an index of carbon footprint using method of reflections • Hidalgo and Hausmann (2009) argue that the method of reflections can be generalized by using different values for the variables Kc,0 and Kp,0 • Apply method of reflections using Kc,0 as the carbon emission per capita of country c, measured in metric tons per capita and available from the World Bank’s World Development Indicators database. Revised method of reflections to estimate carbon foot‐print works of art footwear food & beverages wood leather miscellaneous manufacturing vegetables precious stones & metals plastic & rubber paper machinery & electrical equip. textiles optical, photo, watches, musical instr. stone, ceramic, glass vehicles, aircraft, vessels Live animals base metals animal & vegetable oils minerals chemicals arms & ammunition -4 -2 0 2 Index of carbon footprint (global mean=0, sd=1) 4 .8 .6 0 .2 Density .4 -4 -2 0 Index of carbon footprint (mean=0, sd=1) Bangladesh Thailand 2 Republic of Korea Average of distribution of index of carbon footprint -2 -1.5 -1 -.5 0 USA DEU GBR FRA JPN CHE CHN AUT SWE CAN DN IN DK KORAUS ITA BELNLD ESP CZEZAF SGP FIN HKG POL BRA NOR TUR ISR IRL MEX THA HUN RUSMYS PRT ARE NZL SVN SVKGRC IDN ARG ROU LUX BGR LTU EST UKR PHL VNM HRV LVACOL CHL SRB PER PAN SAU PAK MAR EGY KEN TU CYP CR IN ISL LKA IR N LBN BLR GTM ATG URY PRK BIH SWZMLT MKD VEN ECU MUS DOM SYR TTO KAZ BRB SLV JOR BHR MDA BGD ARM NPL TZA QAT NGA HND GEO KWT ZWE DZA BWAOMN BOL ZMB ALBGHA UZB FJI JAM STP NAM KHM AGO MOZ AZE CIV MNG COD SEN BHS ETH PRY TKM COG SU R CUB KGZ NIC GAB BRN MMR SYC SDN CMR LBY TJK DMA LCA BTN BLZ IRQ D JI GU Y TGO MH LMDV GRD KNA ER I HTI GNQ SLB YEM KIR BEN VU T WSM TLS GMB VCT CPV GNB COM TON LSO 0 10000 20000 Diversification, 2010 (Number of products in the product mix) 30000 Empirical questions 1) Which economic activities are more likely to emerge given the existing technologies in the economy? – Method of proximity (Product Space), revised (RCA not used), cut‐off<=85%, trade data disaggregated by unit code and price range 2) Which of those have higher productivity? – Method of reflections, revised (RCA not used), cut‐ off<=country’s average 3) Which of those are greener? – Method of reflections, revised (RCA not used, CO2 per capita) High correlation between complexity and carbon foot-print (it is not possible to decouple productivity and emissions of existing production) . cor complexity (obs=43289) cfp | complexity cfp -------------+-----------------complexity | 1.0000 cfp | 0.9948 1.0000 Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). Construct: Low carbon growth: creation of new economic activities that have carbon footprint below global average levels (greener economic activities) Global average economic activities in the world Carbon footprint x1 c1 x2 + c2 x3 + c3 n xN … … + cN XN+1 = N+1 Y + c 500 30000 15000 6000 300 0 NUmber of new opportunities 100 200 300 400 Diversification (number of existing products) Total Higher complexity and green Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). Higher complexity UKR NZL IRL ARG BGR ROU NOR GRC IDN ISR ARE PRT SVN MYS RUS SVK FIN HKG THA MEX BRA ZAF TUR AUS HUN POL IND SGP CZE CAN CHN SWE DNK AUT ESPBEL JPN CHE 15000 6000 300 NLD Diversification (number of existing products) Source: Author based on data from the United Nations Commodity Trade Statistics Database (COMTRADE). ITA FRA DEU GBR USA 30000 KOR 0 Proportion of new opportunities with higher complexity that are greener (%) 10 20 30 40 50 60 70 80 90 100 ABW BGD FLK BTN FRO BEN FJI GNB GUM GMB GRL PYF HTI G GUY AB GHA ISL IRQ KIR JAM ESH WLF VUT YEM UZB TUV TON TLS TCA TKL TKM TGO COM COK CUB AIA BDI ERI TCD GNQ DJIDMA CPV CYM BRN BFA CMR SPM SHN KNA LSO WSM VCT STP LBR RWA MDV LCA LBY MDA LAO MWI MDG MAC ALB MHL MYT MRT SYC FSM MSR MNG MNE MMR MOZ NFK MNP PCN NIU NER NGA PLW PSE PNG PRY SOM SLB SDN SUR BHR ATG VGB MKD CIV NIC BRB ZMB NPL QAT TZA ZWE DZA SEN NAM VEN SMR COD KHM MUS AGO KGZ MLI ANT BHS AZE GRD KAZ TJK ASM SLE MLT SWZ ARM OMN HND GEO SYR BLZ BLR BOL URY ECU ETH AND SLV NCL BWA CYPIRN LKAMARPAK GIB DOM EGY NRU BMU PRK BIHLBNTUN TTO VAT COG AFG UGAKWTJOR PHL PER GTM KEN VNM CRI SAUSRB CHL CAF PAN EST GIN LTU LVA HRV COL LUX Thank you [email protected]
