Financial Silk Road to Africa
|
|
- Garey Hines
- 5 years ago
- Views:
Transcription
1 Financial Silk Road to Africa Jacopo Ponticelli Andrea Presbitero September 21, 2017 PRELIMINARY and INCOMPLETE Abstract Notwithstanding the increasing importance of Chinese development finance for several African countries, there is still limited systematic evidence of its impact on recipient countries. We provide new micro-level evidence on the effects of Chinese financing on local economies by matching more than 2,400 project-level data on Chinese official development finance with firm-level data on more than 11,000 firms in 32 Sub-Saharan African countries. We exploit differences in Chinese development finance across sub-national regions, and input-output linkages to show that Chinese-financed development projects had a positive effect on firm sales and labor productivity in recipient economies, especially those operating in non-tradable sector and those operating along the production chain of the development projects. Keywords: Development finance; China; Africa; Firms; Growth. JEL Classification: O12; O14; O22; O55. This research is part of a project on Macroeconomic Research in Low-Income Countries (project id: 60925) supported by the U.K. s Department for International Development (DFID). The views expressed in this paper are those of the authors and do not necessarily represent those of the IMF, IMF policy, or of the DFID. Tao Chen and Ariza Gusti provided excellent research assistance. Ponticelli: Northwestern University and CEPR, jacopo.ponticelli@kellogg.northwestern.edu. Presbitero: International Monetary Fund and MoFiR, APresbitero@imf.org. 1
2 I Introduction China development finance targeting African countries has grown exponentially since the early 2000s. Figure I reports total Chinese lending to African countries, as well as its composition, between 2000 and As shown, Chinese lending can take different forms: loans issued by Chinese development banks and other state-owned firms, grants, technical assistance and export credits. In particular, bank loans account for 70% of total Chinese development finance in Africa since 2000, and have grown from less than 1Bn USD in 2000 to 16 Bn USD in 2010, with a peak of 29 Bn USD in 2012 (AidData 2017, numbers in constant 2014 USD). Chinese development finance can improve local infrastructure and promote economic growth in African countries. 1 However, despite the increasing magnitude of these financial flows, there is scarce empirical evidence on its effects on recipient economies. Figure I: Chinese Development Finance to African Countries, by Type Billion 2014 constant USD Loans Grant Debt forgiveness Technical assistance/training Export credits Other Source: AidData, 2017 In this paper we study the effect of Chinese development finance on firms operating in recipient economies. Whether development finance should benefit or harm local firms is an open empirical question. The data shows that companies implementing Chinese-financed projects in Africa are often Chinese firms. In addition, the financing of the project itself can be conditional on using Chinese contractors or Chinese imported materials. Therefore, to the extent that development finance is implemented by foreign companies and favors import of Chinese goods, it might have no positive effect on local firms or even penalize those operating in the tradable 1 According to recent estimates, in Africa there are more than 10,000 Chinese firms, and China is the biggest trade partner and the largest bilateral infrastructure financier in the continent (Sun et al., 2017). 2
3 sector. As a matter of fact, during the period under study, Chinese exports to African countries increased from 20Bn USD in 2000 to 237Bn USD in 2010, and totaled 419Bn USD in 2014 (see Figure II). 2 In addition, there is a positive correlation between flows of development finance and Chinese exports to recipient countries, as shown in Figure III Figure II: Chinese Exports to African Countries Billion USD Source: COMTRADE. One the other hand, there are several channels through which development finance can benefit firms in recipient economies. First, it can improve local well-being in regions where projects are implemented by generating jobs and increasing wages, which should benefit local firms operating in the non-tradable sector. Second, to the extent that some inputs are sourced locally, it can generate positive demand shocks and incentive to upgrade technology for firms operating along the production chain of the development project. Finally, it can ameliorate local infrastructure for example by providing better road connections or more reliable electricity supply which in turn benefits local firms. To test these channels, we use a new loan-level dataset tracking Chinese-financed projects in African countries between 2000 and We match this dataset with firm-level data from the World Bank Enterprise Survey as well as shipment data at product and destination-country level covering all Chinese exports to African countries. We find positive effects of Chinese-financed development projects on local well-being. Absent reliable measures of income per capita at local level, we use sales by firms operating in the nontradable sector as a measure of local consumption, under the assumption that non-tradable goods tend to be consumed locally. We find that firms located in regions receiving Chinese- 2 African countries constitute a small fraction of Chinese exports to the rest of the world in terms of volume, bust their share has also increased in the last decade, going from 1% of total value of Chinese exports in 2000, to 1.9% in 2010, and to 2.2% in
4 Figure III: Chinese official development finance and exports to recipient countries ODF from China (as a % of GDP, average ) ZWE TON FJI WSM DMA VUT TKM CUB ERI ETH MRT GRD LAO COG GUY VEN NER JAM MDV LKA CIV SLE MOZ KEN GHA TCD BDI CMR AGO MNE MUS CAF BLR RWA COM SSD GNB MLI BOL ECU MWI SDN ZMB SUR LCA GIN MKD SRB KAZ MMR GNQ SYC AFGPAK UGA BIH CPV ARGLSO TZA UZB GAB ALB CRI NICSEN NPL NAM TLS BHS MDG BGD MDA ARM BRA BGR COD RUS LBY NGA PNG YEM AZE BRB IRN UKR PSEROU TTO CHL COL TUR IRQ DZA HTI GEO IND MAR MEX ISR AUS EGY IDN JORMYS KWT STP TUN PER NZL ZAF SYR LBN BRN URY BHR SOM CYP THA Chinese official development finance and exports KHM VNM SGP MNG TJK LBR Imports from China (as a % of GDP, average ) MLT BEN DJI TGO KGZ ATG Source: AidData China Global Data and IMF Direction of Trade Statistics. financed development projects experienced larger increases in sales, and these effects are larger for firms operating in the non-tradable sector relative to those operating in the tradable sector. Next, we investigate if Chinese development finance generate positive demand growth for local input-supplier that operate along the production chain of the development project. To this end, we build a measure of exposure of local firms to the Chinese-driven demand shock for inputs. We find that firms with larger exposure to Chinese-finance projects experienced larger increase in sales and labor productivity. Taken together, our results indicate that Chinese-financed development projects had a positive effect on firm sales and labor productivity in recipient economies, especially those operating in non-tradable sector and those operating along the production chain of the development projects. The timing of these effects suggest tat they are not driven by pre-existing trends and that they are relatively short lived. To the best of our knowledge, this is the first paper to analyze with micro-data the effect of Chinese development finance on firms operating in recipient countries. While there are works that look at the macroeconomic effects of Chinese aid in a cross country framework (Busse et al., 2016; Kilama, 2016), Dreher et al. (2016) is the closest to our analysis. They use nighttime light emissions at the regional level in Africa to show a positive short-run impact of Chinese aid on local development across African sub-national units. While their approach is intended to test for the economic consequences of political favoritism, our analysis directly looks at the firm response to an increase in Chinese development finance, exploiting both regional variations and input-output linkages. In this way, we are able to provide novel evidence on the mechanisms through which Chinese financed development projects could affect local economies. 4
5 Our paper builds also on extensive literature on aid effectiveness (see Rajan and Subramanian, 2011; Clemens et al., 2012; Dreher and Lohmann, 2015; Galiani et al., 2017, among others). 3 Finally, we also contribute to the emerging literature on Chinese lending, which so far mostly focuses on its drivers (Chen et al., 2016; Dreher et al., 2016). II Background and Data Description We merge project-level data on Chinese official development assistance to Africa with firmlevel data from the World Bank Enterprise Survey (WBES). 4 The match is done at the region and sector level. We use the location variable ( a3ax ) of each firms in the WBES and convert it to the standard classification at the first sub-national administrative level (ADM1). We are label to localize almost all (30,313) firms out of the 30,965 firms in 170 ADM1 region in Sub-Saharan Africa. We do the same exercise for Chinese projects: in this case we complement the information available in the original dataset which we convert into ADM1 regions with information on location that we can obtain from the title and the description of the project. We are able to localize 1,363 projects in 282 Sub-Saharan African regions. Figures IV and V show the spatial distribution of firms and Chinese projects, respectively. Figure IV: Firm location in Sub-Saharan Africa Source: World Bank Enterprise Survey; sub-national regions are defined at the ADM1 level. 3 See Qian (2015) for a review of the evidence of the impact of aggregate foreign aid and for a discussion of the problems related to examing aggregate aid flows. 4 We use the Standardized Dataset available online at downloaded in June
6 Figure V: Location of Chinese projects in Sub-Saharan Africa Source: AidData; sub-national regions are defined at the ADM1 level. At the sector level, we take the ISIC classification (Rev. 3.1) as reference for the match, since it is already present (at 4-digit) in the WBES. We manually allocate the Chinese investment project to the corresponding ISIC sector (2-digit) using the information included in the title and description of the project. The match is done considering 17 sectors. 5 Data on Chinese development finance to Africa come from AidData: Tracking Chinese Development Worldwide, a new dataset that contains project-level information on Chinese official development finance (loans, grants, debt forgiveness, export credit) to Africa, Asia and Latin America from 2000 to Africa is the largest recipient, both in terms of number of projects and value, especially since 2011 (Figure VI). Overall, the dataset includes 2,469 projects financed in Africa since 2000, with Zimbabwe, Angola, Tanzania, Ghana, Liberia, Kenya, Ethiopia, and Zambia being the countries that attracted the largest number of projects (Table I). Contrary to the common wisdom that Chinese investments are concentrated in oil, gas, and extractive industries, the sectoral distribution of Chinese projects shown in Table II points to a much more diversified investment pattern across sectors, with a prevalence of 5 The sectors, constructed aggregating the 2-digit ISIC ones, are: Agriculture, forestry and fishing; Mining; Manufacturing; Electricity, gas, and water supply; Construction; Wholesale and sale of motor vehicles; Retail trade, except of motor vehicles; Hotel & restaurants; Transport and storage; Information and communication; Financial intermediation and real estate and renting; Business activities; Public administration; Education, health and social works; Other services; Private household activities; Extra-territorial organizations. 6 The dataset builds on a previous version, which collects data until 2011 and is carefully discussed by Strange et al. (2017). We exclude all projects that are categorized as pledges, and those that have been suspended or canceled. 6
7 Figure VI: Chinese Development Finance: Number of Projects and Value Number of transactions Values Number of transactions Billion 2014 constant USD Latin America and the Caribbean Southeast Asia Middle East Central and North Asia Africa South Asia Europe The Pacific Latin America and the Caribbean Southeast Asia Middle East Central and North Asia Africa South Asia Europe The Pacific Notes: The left-hand side panel reports the regional distribution of development projects, while the right-hand side chart plots the corresponding vales, in billion of 2014 constant USD; some projects recorded in the dataset do not have information on loan amount. All canceled and suspended transactions are excluded, as well as pledges of official finance. Data on development finance include all flows (loans, grants, debt forgiveness, export credit, etc.). Source: AidData China Global Data. projects in manufacturing, health and social works, and education (Parks, 2015). 7 Since we are interested in improvements in local well-being, and the WBES has a limited panel dimension, we exploit the fact that each survey asks the level of total sales and employment in the year of the survey and three fiscal year before. Additional documentation provided by the World Bank specifies the exact year to which the question refer to. In most cases, the gap between the two points in time is two calendar year, while in a few cases the difference is three ears. For uniformity, we consider all the survey with the same gap in the reporting of current and past levels of employment and sales and we chose two years to maximize the sample size. In this way, we can compute the percentage change in employment, sales and labor productivity (defined as sales per employee) over a three year period. III Empirics In this section we study the effect of Chinese development finance on firms operating in African recipient economies. We investigate two main channels through which development finance can affect local firms. First, we study the effect of development finance on local firms through increases in local demand. To the extent that Chinese investments create new jobs and higher wages in the regions where they are implemented, they can translate into higher consumption and, therefore, higher demand for firms operating in the non-tradable sector. Second, we study the effect of development finance on local firms through input-output linkages. Chinese investment in certain sectors can generate demand for inputs produced by firms in the 7 Similar evidence on the lack of concentration of investment in resource extraction is also discussed by McMillan (2017) with respect to foreign direct investment. 7
8 Table I: Chinese Development Finance to Africa, Top Recipients Notes: The table reports the top recipients of Chinese development finance, in terms of number of projects, between 2000 and The last column reports also the total value of projects received by each country, in billion of constant 2014 USD; some projects recorded in the dataset do not have information on loan amount. All canceled and suspended transactions are excluded, as well as pledges of official finance. Data on development finance include all flows (loans, grants, debt forgiveness, export credit, etc.). Source: AidData China Global Data. Country # projects Value Zimbabwe Angola Tanzania Ghana Liberia Kenya Ethiopia Zambia Uganda Sudan Cameroon Congo, Rep Namibia Rwanda Mali Sierra Leone Niger Mozambique Burundi Nigeria recipient economy that operate along the production chain of the development project. III.A Local Demand We start by investigating the local demand channel. Development finance in a given region can improve local well-being by increasing demand for workers employed in the financed project itself, thus increasing local wages. To the extent that higher local income translate into higher consumption, the demand for non-tradable goods should increase, under the assumption that non-tradable goods tend to be consumed locally. In order to test this hypothesis we estimate the following equation: log(y NT irct) t 1,t+1 = α r + α t + βcdf rct + ε irct (1) where i identifies a firm, r identifies a region within a country (the first administrative division, ADM1), c identifies a country, and t identifies time. The variable log(y NT irct) t 1,t+1 in equation (1) is the change in the log of a firm-level outcome between year t 1 and year t+1. We focus on three main firm-level outcomes: sales, employment and labor productivity measured as the ratio of sales over number of workers. In order to test the local demand channel, in this 8
9 Table II: Chinese Development Finance to Africa, by Sector Notes: The table reports the sectoral distribution of Chinese development finance, in terms of number of projects and value, between 2000 and Project value is available only for a sub-set of 1,122 project and it is expressed in billion of constant 2014 USD. All canceled and suspended transactions are excluded, as well as pledges of official finance. Data on development finance include all flows (loans, grants, debt forgiveness, export credit, etc.). Whenever possible, each project have been classified into a sector based on the title and description of the project. Sectors are based on the ISIC Rev 3.1 classification. Source: AidData China Global Data. # projects Value Agriculture Fishing Mining Manufacturing Electricity Construction Transport and communication Financial intermediation Real estate and business activities Public administration Education Health and social works Other services Private household activities Total 2, specification we restrict our sample to firms operating in the non-tradable sector (N T ). The coefficient of interest is β, which captures the effect of Chinese development finance (CDF) in region c at time t on the change in firm-level outcomes between the year before (t 1) and year after (t + 1) the year of implementation of the development project (t). The variable CDF is measured as number of projects. 8 Table IV reports the results obtained estimating equation (1) for firms operating in the services sector, which tend to be mostly non-tradable. 9 We start by studying the relationship between Chinese development finance and firm-level changes in sales. Columns 1 and 2 report the results. Our estimates indicate that firms operating in regions with a larger number of Chinese-financed development projects experienced a larger increase in sales. The magnitude of the estimated coefficient reported in column 2 suggests that firms operating in regions with one additional project experienced a 20 percent larger increase in sales between the year before and the year after the implementation of the project. Next, we focus on the effect of development finance on firm labor productivity and employment. Labor productivity is measured as the log of sales per worker. As shown, for labor productivity we find effects of similar size as those for sales, while we find small and non statistically significant effects of development finance on 8 We obtain similar and, for certain outcomes, larger magnitudes when using total value of loans as our measure of Chinese development finance. However, we prefer to use the number of projects as our measure of CDF in the baseline specification because for several projects the loan value is missing in the original data. 9 The World Bank Enterprise Survey directly identifies firms operating in manufacturing and services, the latter including wholesale, retail, IT, hotels and restaurants and other services 9
10 employment. Notice that we can not give a causal interpretation to the coefficients presented in Table IV. Higher firm-level growth in sales of non-tradable goods after the introduction of Chinesefinanced projects could be driven by forces other than the income effect generated by the Chinese-financed project itself. In addition, Chinese development institutions or the recipient country government might select a certain region for a given project based on its current performance. In that sense, our result would be explained by the allocation of development finance to regions that are experiencing larger growth ex-ante. We can partially deal with these concerns by presenting additional evidence consistent with our hypothesis. First, if local firm growth is generated by larger consumption, then we should observe larger growth of firms operating in non-tradable sector relative to the tradable sector. We test this by estimating equation 1 on the sample of firms from the World Bank Enterprise Survey that operate in the manufacturing sector. This is because manufacturing goods tend to be tradable, across regions and across countries. Results are reported in Table V. As shown, the coefficients on the number of Chinese-financed development projects when the outcome is sales growth of manufacturing firms are half the size with respect to those presented in Table IV. Second, we investigate the timing of the effect of Chinese development finance on firm-level outcomes. To this end, we augment equation (1) by adding two-years lag and two-years lead of the number of Chinese financed-projects. The results are reported in Table VI. As shown, firm sales growth between year t 1 and year t + 1 is not a predictor of the number of Chinese-financed projects that will be implemented in a given region (at time t + 2). This result mitigates the concern that our estimates are driven by reverse causality: Chinese-finance projects being allocated to regions with larger sales growth ex-ante. 10 At the same time, our results indicate that, if any, the effect of Chinese-financed projects are relatively short lived, as there is no effect of development finance at t 2 on firm sales growth between t 1 and t + 1. III.B Production Chain In the previous section we showed that Chinese-financed projects had a positive impact on sales of local firms, and that these effects are larger for firms operating in the non-tradable sector. In this section we study the effect of Chinese development finance on firms in recipient economies through input-output linkages. Depending on the sector in which a development project is implemented, it can potentially generate an increase in demand for goods produced by firms that operate along the production chain of that project. In order to test this hypothesis we construct a firm-level measure of exposure to Chinese development finance through inputoutput linkages and estimate the following equation: 10 Aggregate evidence at the country level also indicates that Chinese investment are uncorrelated with growth expectations. Figure VII plots official development flows (as a share of GDP) in year t against the average IMF growth forecast in year t for the period t + 1 to t + 3, and it shows no correlation between the two variables. 10
11 Figure VII: Chinese official development assistance and growth expectations 20 ZWE ODF from China (as a % of GDP) ERI ERI LBR TGO MUS COM ZWE MRT GNB GIN NER SLE CIV KEN ETH CMR TCD SYCOG BDI CAF COG ZWE KEN MOZ LBR ETH GNQ MRT RWA RWA SDN TZA ZWE COG GNB BDI AGO BEN CPV MLILBR GHA MWI ETH ETH LBR COG CMR AGO CMR COG GHA CIV ETH GHA ZWE COM ZMB MOZ MOZ SDN TCD CAF CMR CPV GNQ LSO COM MLI UGA MOZ GNQ LSOAGO BDI BDI CAF CMR GHAMRT RWA UGA MUS ZMB SYC TGO ERI COD ETH COG COM CMR GHA GIN ZMB GIN SLE ZMB GNB UGA MLI NER CAF AGO AGO BDI BDI ETHGAB GNBMDG GHA LBR GAB LSO COG BDI AGO AGO AGO BWA BWA CAF BDI BDI BDI CIVBWABWA CIV COGCOM GHA GAB LBRGNQ KEN BDI CAF BWABEN CIV CIV CAF BEN BDI CIV CAF BDI BEN CIV CIV CMR COD CMRCMR BEN BWA CIV CMR ETHCPV ERI ERI ERI ETH BDI BWA BEN AGO AGO COD COD COM CPV COM CPV COG COG ERI ERIETH CPV COGCPV ETH COG ETH ETH GAB GAB GHA GHA LBRGHA KEN GNQ GIN GHA GNQ GAB GAB GNB GAB GNB GAB GNB GIN GNB GIN GNB GIN GIN GIN GIN GAB CPV GNB CODCOD GHA ERI CPV ETH GHA GNQ GNQ GNQ KEN KEN KEN KEN KEN KEN KEN LBR LBR LBR LBR KEN LSO LSO LSO MLI LSO MLI MLI MWI MOZ NAM MDG MDG MDGMOZ MOZ MUS MWI NAM NAM RWATZA NER ZWE SDN SEN MLI MOZ MUS MWI NGA MOZ MOZ MUS LSO MDG LSO MDGMDGMDG LSO KEN GNQ KEN MLI LSO LSO MLI MOZ MRT MRT MRT MDG MDG MOZ MRT MUS MWI MUSMUS MWI NAM NAM NAM NER NAM NER NAM SDN SLE UGA SDN NER RWA NER NGA NER NERNER NAM NGA NGA RWA NGA MUS MUSNGA MWI NGA RWA NER NGA SDN SEN RWA RWA RWARWA RWARWA SDN SDN SDN SEN SEN SEN SLE SLE TGO SLE SLE SYC SYC TGO TGO SLE TCD SLE NGA MOZ MRT SDN TCD SYC TGO SYC SYC TGO TCD TGO TZA TGOTGO SENSEN SLE SDN SDN TGO TZA SLESLE TZA TZA ZMB TZA UGA ZAF ZAF ZAFZAF ZWE ZAF ZMBZMB ZMB ZMB ZWE ZMB ZWE ZWE ZWE ZMB UGAUGA UGA TZA SLE UGA TZA TCDTZA COD TZACOG AGO GNQ BWA MOZ SDN GIN MRT Average growth forecast over t+1 and t+3, as in April WEO of year t Source: AidData China Global Data and IMF World Economic Outlook (different April vintages). log(y ijct ) t 1,t+1 = α j + α t + β j w jj CDF j t + ε r (2) where i indexes firms, j indexes sector, c indexes country and t indexes time. Our measure of exposure to development finance through input-output linkages is defined as sector-level. The weight w jj captures the exposure of sector j to sector j through input-output linkages. We define this weight as the share of inputs that sector j buys from sector j divided by the total value of inputs used by sector j. In order to construct these weights, we use the inputoutput table of the United States for the year 2000, which pre-dates the period of analysis of this paper. The measure of exposure is just the weighted sum of the number of development projects implemented in all sectors j that operate downstream with respect to sector j, i.e. all those sectors buying inputs from sector j. Table VII reports the results obtained estimating equation (2). We start by studying the relationship between exposure to Chinese development finance via input-output linkages and firm-level changes in sales. Columns 1 and 2 report the results. Our estimates indicate that firms operating in sectors that are more exposed to development projects experienced a larger increase in sales. The magnitude of the estimated coefficient reported in column 2 indicates that firms operating in sectors with a one standard deviation higher exposure to Chinese-financed 11
12 development projects through input-output linkages experienced a 21.6% larger increase in sales between the year before and the year after the implementation of the project. These firms experienced an increase in labor productivity of similar magnitude, while we find no effect of the production chain channel on firm employment. IV Final Remarks Chinese lending to Africa has markedly increased over the last decade. While Chinese financing can contribute to infrastructure development and promote growth, it is also fraught with controversy. So far, there is no clear evidence on the effects of Chinese lending on recipient economies. To shed light on this debate, we provide new empirical evidence on the effects of Chinese financing on local economies, based on project-level data on Chinese development finance, matched with firm-level information. First, we find that firms operating in regions that received a Chinese-financed projects experienced a higher sales growth than those located in regions without Chinese projects. As this effect is stronger for service than for manufacturing firms, we interpret it as evidence suggesting that Chinese financing improve local consumption. Second, we show that firms active in sectors more exposed to Chinese development financing growth more in response to an increase in Chinese financing. Both our results indicate that Chinese-financed development projects could have positive effects on local economies, thanks to an increase in firm growth and labor productivity, even though there are no discernible effects on jobs. However, our findings can not be interpreted is a causal way, given that the allocation of projects may not be random, but related to economic prospects. Suggestive evidence on the distribution of projects across countries does not indicate that this is in fact the case. To have a more convincing identification strategy, further analyses will tackle the endogeneity issue in a more formal way. In addition, we will also expand the scope of our work, considering the effect of Chinese financing on trade flows at the firm level. 12
13 References AidData (2017). Tracking China Development Finance Worldwide Dataset. Busse, M., C. Erdogan, and H. Mühlen (2016). China s Impact on Africa The Role of Trade, FDI and Aid. Kyklos 69 (2), Chen, W., D. Dollar, and K. Tang (2016). Why Is China Investing in Africa? Evidence from the Firm Level. World Bank Economic Review Forthcoming. Clemens, M. A., S. Radelet, R. R. Bhavnani, and S. Bazzi (2012). Counting chickens when they hatch: Timing and the effects of aid on growth. The Economic Journal 122 (561), Dreher, A., A. Fuchs, R. Hodler, B. C. Parks, P. A. Raschky, and M. J. Tierney (2016). Aid on Demand: African Leaders and the Geography of China s Foreign Assistance. Working Paper 3 (revised), AidData. Dreher, A. and S. Lohmann (2015). Aid and growth at the regional level. Oxford Review of Economic Policy 31 (3-4), Galiani, S., S. Knack, L. C. Xu, and B. Zou (2017). The effect of aid on growth: Evidence from a quasi-experiment. Journal of Economic Growth 22 (1), Kilama, E. G. (2016). The influence of China and emerging donors aid allocation: A recipient perspective. China Economic Review 38, McMillan, M. (2017, July). Chinese investment in Africa. VoxDev, July 21. Parks, B. C. (2015, November). 10 Essential Facts About Chinese Aid in Africa. The National Interest. Qian, N. (2015). Making Progress on Foreign Aid. Annual Review of Economics 7, Rajan, R. G. and A. Subramanian (2011). Aid, Dutch disease, and manufacturing growth. Journal of Development Economics 94 (1), Strange, A. M., A. Dreher, A. Fuchs, B. C. Parks, and M. J. Tierney (2017). Tracking Underreported Financial Flows: China s Development Finance and the Aid Conflict Nexus Revisited. Journal of Conflict Resolution 61 (5), Sun, I. Y., K. Jayaram, and O. Kassiri (2017, June). Dance of the lions and dragons. McKinsey & Company. 13
14 Tables Table III: Summary Statistics variable name mean median sd N Panel A: Services firms log Sales t 1,t ,585 log Sales L t 1,t ,585 log L t 1,t ,585 CF D t ,585 Panel B: Manufacturing firms log Sales t 1,t ,170 log Sales L t 1,t ,170 log L t 1,t ,170 CF D t ,170 Panel C: Production Chain log Sales t 1,t ,344 log Sales L t 1,t ,344 log L t 1,t ,344 CF D t ,344 Notes: Sources are World Bank Enterprise Survey and AidData - Tracking Chinese Development Worldwide dataset. 14
15 Table IV: Local Demand Channel: Services Firms (1) (2) (3) (4) (5) (6) VARIABLES log Sales t 1t+1 log Sales log L L t 1t+1 t 1t+1 CDF in the region (n loans) t 0.116** 0.108** 0.113** 0.106** [0.046] [0.044] [0.043] [0.041] [0.007] [0.007] Observations 6,585 6,582 6,585 6,582 6,585 6,582 R-squared Sector FE Yes - Yes - Yes - Year FE Yes - Yes - Yes - Sector year FE No Yes No Yes No Yes N clusters Notes: Standard Errors are clustered at the country-year level. Significance levels: *** p<0.01, ** p<0.05, * p<0.1. Table V: Local Demand Channel: Manufacturing Firms (1) (2) (3) (4) (5) (6) VARIABLES logsales t 1t+1 log Sales logl L t 1t+1 t 1t+1 CDF in the region (n loans) t 0.082* 0.082* 0.076* 0.076* [0.042] [0.042] [0.039] [0.039] [0.007] [0.007] Observations 5,170 5,170 5,170 5,170 5,170 5,170 R-squared Sector FE Yes - Yes - Yes - Year FE Yes - Yes - Yes - Sector year FE No Yes No Yes No Yes N clusters Notes: Standard Errors are clustered at the country-year level. Significance levels: *** p<0.01, ** p<0.05, * p<
16 Table VI: Demand Channel: Timing of the Effect (1) (2) (3) (4) (5) (6) (7) (8) (9) log Sales t 1t+1 log Sales L t 1t+1 log L t 1t+1 VARIABLES all firms Serv Manuf all firms Serv Manuf all firms Serv Manuf CDF in the region (n loans) t * ** * * * * [0.099] [0.108] [0.073] [0.100] [0.109] [0.071] [0.010] [0.012] [0.010] CDF in the region (n loans) t 0.195*** 0.238*** 0.169** 0.194*** 0.231*** 0.171*** [0.068] [0.076] [0.065] [0.066] [0.074] [0.063] [0.007] [0.008] [0.007] CDF in the region (n loans) t [0.088] [0.096] [0.088] [0.082] [0.090] [0.082] [0.010] [0.010] [0.011] Observations 9,983 5,550 4,430 9,983 5,550 4,430 9,983 5,550 4,430 R-squared Sector FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Sector year FE No No No No No No No No No N clusters Notes: Standard Errors are clustered at the country-year level. Significance levels: *** p<0.01, ** p<0.05, * p<
17 Table VII: Production Chain Channel: Baseline (1) (2) (3) (4) (5) (6) VARIABLES log Sales t 1t+1 log Sales log L L t 1t+1 t 1t+1 CDF Exposure - IO Linkages (n loans) t 0.200* 0.242** 0.209** 0.252** [0.105] [0.116] [0.097] [0.106] [0.016] [0.019] Observations 11,344 11,340 11,344 11,340 11,344 11,340 R-squared Sector FE Yes - Yes - Yes - Year FE Yes - Yes - Yes - Sector year FE No Yes No Yes No Yes N clusters Notes: Standard Errors are clustered at the country-year level. Significance levels: *** p<0.01, ** p<0.05, * p<0.1. Table VIII: Production Chain Channel: Robustness (1) (2) (3) (4) (5) (6) VARIABLES log Sales t 1t+1 log Sales log L L t 1t+1 t 1t+1 CDF Exposure - IO Linkages (n loans) t 0.235* 0.312** 0.251** 0.314** [0.123] [0.139] [0.111] [0.130] [0.021] [0.021] Exporter ** [0.215] [0.195] [0.227] [0.211] [0.015] [0.020] Med-sized firm, ** 0.110*** [0.055] [0.056] [0.063] [0.063] [0.035] [0.036] Large firm ** 0.178*** [0.108] [0.095] [0.144] [0.140] [0.045] [0.052] Government-owned 0.022* 0.021* [0.012] [0.011] [0.002] Firm age (ln) *** [0.101] [0.101] [0.010] Sole proprietorship 0.170** *** [0.082] [0.081] [0.016] Observations 9,925 8,689 9,925 8,689 9,925 8,689 R-squared Sector FE Year FE Sector year FE Yes Yes Yes Yes Yes Yes N clusters Notes: Standard Errors are clustered at the country-year level. Significance levels: *** p<0.01, ** p<0.05, * p<
Monetary Policy and Financial System During Demographic Change:
Monetary Policy and Financial System During Demographic Change: Three questions Gauti B. Eggertsson Brown University 1. Can demographic change account for worldwide decline in interest rate? 2. What is
More informationProductivity adjustment in ICP
3rd Meeting of the PPP Compilation and Computation Task Force September 27 28, 2018 World Bank, 1818 H St. NW, Washington, DC MC 10-100 Productivity adjustment in ICP Robert Inklaar Productivity adjustment
More informationThe Disappointments of Financial Globalization. Dani Rodrik November 7, 2008 Bank of Thailand International Symposium
The Disappointments of Financial Globalization Dani Rodrik November 7, 2008 Bank of Thailand International Symposium 1 14 12 10 8 6 4 2 0 Financial globalization: flows Gross private capital flows to developing
More informationNBER WORKING PAPER SERIES INTRINSIC OPENNESS AND ENDOGENOUS INSTITUTIONAL QUALITY. Yang Jiao Shang-Jin Wei
NBER WORKING PAPER SERIES INTRINSIC OPENNESS AND ENDOGENOUS INSTITUTIONAL QUALITY Yang Jiao Shang-Jin Wei Working Paper 24052 http://www.nber.org/papers/w24052 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050
More informationTrade led Growth in Times of Crisis Asia Pacific Trade Economists Conference 2 3 November 2009, Bangkok. Session 12
Trade led Growth in Times of Crisis Asia Pacific Trade Economists Conference 2 3 November 2009, Bangkok Session 12 Factors Contributing to Export Performance in the Aftermath of Global Economic Crisis
More informationEconomic Growth: Lecture 1 (first half), Stylized Facts of Economic Growth and Development
14.452 Economic Growth: Lecture 1 (first half), Stylized Facts of Economic Growth and Development Daron Acemoglu MIT October 24, 2012. Daron Acemoglu (MIT) Economic Growth Lecture 1 October 24, 2012. 1
More informationWorld Bank list of economies (June 2017)
1 Afghanistan AFG South Asia Low income IDA HIPC 21 Benin BEN Sub-Saharan Africa Low income IDA HIPC 31 Burkina Faso BFA Sub-Saharan Africa Low income IDA HIPC 32 Burundi BDI Sub-Saharan Africa Low income
More informationInstitutions, Incentives, and Power
Institutions, Incentives, and Power 1 / 30 High Level Institutions Selectorate: The portion of the population that has some chance of playing a role in the selection of the leader. inning Coalition: The
More informationHOW TO RESTART AFRICA S GROWTH ENGINE
HOW TO RESTART AFRICA S GROWTH ENGINE Copyright Institute for Security Studies 22 June 217 Restarting the Growth Engine Regional Economic Outlook for Sub-Saharan Africa African Department International
More informationRestarting the Growth Engine Regional Economic Outlook for Sub-Saharan Africa. African Department International Monetary Fund May 2017
Restarting the Growth Engine Regional Economic Outlook for Sub-Saharan Africa African Department International Monetary Fund May 217 Outline Adjustment Financing A Broad-based Slowdown Insufficient Adjustment
More informationDoes Country Size Matter? (Short Note)
World Bank From the SelectedWorks of Mohammad Amin June 3, 2011 Does Country Size Matter? (Short Note) Mohammad Amin Available at: https://works.bepress.com/mohammad_amin/36/ Does Country Size Matter?
More informationChapter 6. Macroeconomic Data. Zekarias M. Hussein and Angel H. Aguiar Uses of Macroeconomic Data
Chapter 6 Macroeconomic Data Zekarias M. Hussein and Angel H. Aguiar This chapter provides an overview of the macroeconomic features of the 8 Data Base. We will first present how the macroeconomic data
More informationCREI Lectures 2010 Differences in Technology Across Space and Time
CREI Lectures 2010 Differences in Technology Across Space and Time Francesco Caselli Barcelona, June 16-18 1 / 77 General Introduction 2 / 77 Adam Smith would be surprised 3 / 77 Adam Smith would be surprised
More informationECON 385. Intermediate Macroeconomic Theory II. Solow Model With Technological Progress and Data. Instructor: Dmytro Hryshko
ECON 385. Intermediate Macroeconomic Theory II. Solow Model With Technological Progress and Data Instructor: Dmytro Hryshko 1 / 35 Examples of technological progress 1970: 50,000 computers in the world;
More informationRelative Prices and Sectoral Productivity
Relative Prices and Sectoral Productivity Diego Restuccia University of Toronto and NBER University of Oslo August 4-8, 27 Restuccia Macro Growth and Development University of Oslo / 37 Overview Relative
More informationForeign Capital and Economic Growth
Foreign Capital and Economic Growth Arvind Subramanian (Eswar Prasad and Raghuram Rajan) Western Hemisphere Department Workshop November 17, 2006 *This presentation reflects the views of the authors only
More informationNBER WORKING PAPER SERIES GLOBAL SAVINGS AND GLOBAL INVESTMENT: THE TRANSMISSION OF IDENTIFIED FISCAL SHOCKS. James Feyrer Jay C.
NBER WORKING PAPER SERIES GLOBAL SAVINGS AND GLOBAL INVESTMENT: THE TRANSMISSION OF IDENTIFIED FISCAL SHOCKS James Feyrer Jay C. Shambaugh Working Paper 15113 http://www.nber.org/papers/w15113 NATIONAL
More informationGoing beyond regulation: Social Policy and Private Sector Involvement in Water Supply
Going beyond regulation: Social Policy and Private Sector Involvement in Water Supply Naren Prasad Geneva 22 April 2007 Presentation prepared for the workshop entitled Legal Aspects of Water Sector Reforms,
More informationOnline Appendix for Explaining Educational Attainment across Countries and over Time
Online Appendix for Explaining Educational Attainment across Countries and over Time Diego Restuccia University of Toronto Guillaume Vandenbroucke University of Southern California March 2014 Contents
More informationAging, Output per capita and Secular Stagnation
Aging, Output per capita and Secular Stagnation Gauti B. Eggertsson, Manuel Lancastre, and Lawrence H. Summers. 1 ---- Very Preliminary ---- Abstract This paper shows that aging has positive effect on
More informationChapter 6 Macroeconomic Data
Chapter 6 Macroeconomic Data Angel H. Aguiar and Betina V. Dimaranan 6.1 Uses of Macroeconomic Data During the Data Base construction process, macroeconomic data are used in various stages. The primary
More informationRegional and Global Trade Strategies for Liberia
Regional and Global Trade Strategies for Liberia Jaime de Melo FERDI, IGC Armela Mancellari IGC International Growth Centre de Melo, Mancellari Regional and Global Trade Strategies for Liberia Outline
More informationCAN FDI CONTRIBUTE TO INCLUSIVE GROWTH: ROLE OF INVESTMENT FACILITATION
CAN FDI CONTRIBUTE TO INCLUSIVE GROWTH: ROLE OF INVESTMENT FACILITATION Iza Lejarraga Head of Unit, Investment Policy Linkages OECD Investment Division FIFD Workshop on Investment Facilitation for Development
More informationMethodology for a World Bank Human Capital Index
Policy Research Working Paper 8593 Methodology for a World Bank Human Capital Index Aart Kraay WPS8593 Background Paper to the 2019 World Development Report Public Disclosure Authorized Public Disclosure
More informationBy Daron Acemoglu, Simon Johnson, and James A. Robinson, 2001
By Daron Acemoglu, Simon Johnson, and James A. Robinson, 2001 We exploit differences in European mortality rates to estimate the effect of institutions on economic performance. Europeans adopted very different
More informationFiscal Adjustment and Economic Diversification Regional Economic Outlook for Sub-Saharan Africa
Fiscal Adjustment and Economic Diversification Regional Economic Outlook for Sub-Saharan Africa African Department International Monetary Fund November 16, 17 Outline 1. A modest growth recovery 2. Factors
More informationPartial Default. Mpls Fed, Univ of Minnesota, Queen Mary University of London. Macro Within and Across Borders NBER Summer Institute July 2013
Partial Default Cristina Arellano, Xavier Mateos-Planas and Jose-Victor Rios-Rull Mpls Fed, Univ of Minnesota, Queen Mary University of London Macro Within and Across Borders NBER Summer Institute July
More informationEffectiveness of Tax Incentives in Attracting Investment; Evidence and Policy Implications
Effectiveness of Tax Incentives in Attracting Investment; Evidence and Policy Implications Edward Mwachinga Global Tax Simplification Team, World Bank Group February 12 Lusaka, Zambia WBG Tax Simplification
More informationMacroeconomics Econ202A
Macroeconomics Econ202A Pierre-Olivier Gourinchas UC Berkeley Berkeley, Fall 2014 November 18, 2014 1/11 The First Oil Price Shock Nt ten r- ) N % I I I I I I N ~~OcI I 0O N tn ^N Nt tn Nt > I I I I >~~~t
More informationFiscal Policy and Income Inequality. March 13, 2014
Fiscal Policy and Income Inequality March 13, 2014 Inequality has been increasing in most economies 0.55 Disposable Income Inequality: 1980 2010 0.5 0.45 Gini coefficient 0.4 0.35 0.3 0.25 0.2 1980 1985
More informationDoes Aid Affect Governance?
Does Aid Affect Governance? Raghuram Rajan and Arvind Subramanian January 2007 2 I. Channels from Aid to Growth Why is there little robust evidence that foreign aid significantly enhances the economic
More informationIntroduction: Basic Facts and Neoclassical Growth Model
Introduction: Basic Facts and Neoclassical Growth Model Diego Restuccia University of Toronto and NBER University of Oslo August 14-18, 2017 Restuccia Macro Growth and Development University of Oslo 1
More informationIDA16 Mid-Term Review. Capping MDRI Netting Out: Implementation Experience
Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized IDA16 Mid-Term Review Capping MDRI Netting Out: Implementation Experience IDA Resource
More informationStructural Reforms, IMF Programs and Capacity Building: An Empirical Investigation
WP/12/232 Structural Reforms, IMF Programs and Capacity Building: An Empirical Investigation Rabah Arezki, Marc Quintyn and Frederik Toscani 2012 International Monetary Fund WP/12/232 IMF Working Paper
More informationStructural Indicators: A Critical Review
OECD Journal: Economic Studies Volume 21 OECD 21 Structural Indicators: A Critical Review by Davide Furceri and Annabelle Mourougane* This article reviews and assesses, in terms of availability, reliability
More informationAML/CFT reporting Inherent risks 2017 Insurance companies. Page 1 of 22 NBB_2018_01
1. General information Company name: 1.1. [FREE TEXT] Address of registered office (or address of the branch): 1.2. [FREE TEXT] CBE number: 1.3. [FREE TEXT] Member of the statutory governing body (or,
More information40 Chile CHL.. High income: OECD IBRD 41 China CHN East Asia & Pacific Upper middle income IBRD 42 Colombia COL Latin America & Caribbean Upper middle
1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania ALB Europe & Central Asia Upper middle income IBRD 3 Algeria DZA Middle East & North Africa Upper middle income IBRD 4 American Samoa ASM East
More informationGravity, Market Potential, and Economic Development: Supplemental Material
Gravity, Market Potential, and Economic Development: Supplemental Material Keith Head Thierry Mayer October 26, 2010 1 Time-varying linkage coefficients Figure 1 present the schedule of estimated coefficients
More informationMisallocation, Establishment Size, and Productivity
Misallocation, Establishment Size, and Productivity Pedro Bento West Virginia University Diego Restuccia University of Toronto November 15, 2014 1 / 23 Motivation Large Income Differences Across Countries
More information38th Board Meeting Mid-2017 Key Performance Indicator Results For Board Information
38th Board Meeting Mid-2017 Key Performance Indicator Results For Board Information GF/B38/24 Geneva, Switzerland 14-15 November 2017 Contents Executive Summary ANNEX 1: 2012-2016 KPI Framework Results
More informationProcedure for reporting the number of ships issued with certification in accordance with the ISPS Code
No.26 No.26 (May (cont) 2003) (Rev.1 Apr 2004) (Rev.2 Dec 2007) Procedure for reporting the number of ships issued with certification in accordance with the ISPS Code 1 Background This Procedural Requirement
More informationCOMCEC STRATEGY. For Building an Interdependent Islamic World COMCEC FINANCIAL OUTLOOK Fırat YILMAZ. 2nd Meeting of COMCEC Finance Working Group
COMCEC FINANCIAL OUTLOOK 2014 Fırat YILMAZ 2nd Meeting of COMCEC Finance Working Group March 27th, 2013 Ankara, Turkey OUTLINE Recent Financial Developments Financial Outlook of COMCEC Region 2 RECENT
More informationTrade Openness and Output Volatility
MPRA Munich Personal RePEc Archive Trade Openness and Output Volatility Maria Bejan ITAM (Instituto Tecnologico Autonomo de Mexico) February 2006 Online at https://mpra.ub.uni-muenchen.de/2759/ MPRA Paper
More informationInclusive Growth. Miguel Niño-Zarazúa UNU-WIDER
Inclusive Growth Miguel Niño-Zarazúa UNU-WIDER Significant poverty reduction since 1990s Latin America Percentage of people living on less than $1.25 USD fell from 47% (2bp) in 1990 to 24% (1.4bp) in 2008
More informationThe previous chapter described the huge, complicated effort by the International Comparison
CHAPTER 10 Validation of Basic Heading and Aggregated PPPs: When Does Validation End and Estimation Begin? Frederic A. Vogel The previous chapter described the huge, complicated effort by the International
More informationExecutive Directors welcomed the strengthening
IMF EXECUTIVE BOARD DISCUSSION SUMMARY The following remarks were made by the Acting Chair at the conclusion of the Executive Board s discussion of the World Economic Outlook, Global Financial Stability
More informationMaking Finance Work for Africa: The Collateral Debate. World Bank FPD Forum April 2007
World Bank Group Making Finance Work for Africa: The Collateral Debate World Bank FPD Forum April 2007 Sevi Simavi Investment Policy Specialist FIAS, World Bank Group ssimavi@ifc.org Outline Why care about
More informationEXCHANGE RATES AND MARGINS OF TRADE: EVIDENCE FROM CHINESE EXPORTERS
1 EXCHANGE RATES AND MARGINS OF TRADE: EVIDENCE FROM CHINESE EXPORTERS Heiwai Tang (Tufts and LdA) Yifan Zhang (Lingnan) HKIMR, Hong Kong, August 3, 2011 2 Motivation Many regard China's currency policy
More informationShifting Wealth: Economic and Social Challenges
Mario Pezzini, Director, OECD Development Centre Shifting Wealth: Economic and Social Challenges A Regional Comparison UNESCAP February 2015 1 I. Shifting Wealth II. Economic and social challenges III.
More informationHow Will We Know When We Have Achieved Universal Health Coverage?
How Will We Know When We Have Achieved Universal Health Coverage? The Newly Revamped Health Equity and Financial Protection Indicators (HEFPI) Database Adam Wagstaff Research Manager, Development Research
More informationMACROECONOMIC DETERMINANTS OF EXIT FROM AID-DEPENDENCE
MACROECONOMIC DETERMINANTS OF EXIT FROM AID-DEPENDENCE Working Paper number 90 February, 2012 Degol Hailu Economic Policy Advisor, UNDP Admasu Shiferaw Assistant Professor of Economics and African Studies,
More informationENABLING THE BUSINESS OF AGRICULTURE
Ethiopia ENABLING THE BUSINESS OF AGRICULTURE 2017 2017 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington, DC 20433; Telephone: 202-473-1000; www.worldbank.org
More informationForeign Firms, Distribution of Income, and the Welfare of Developing Countries
Foreign Firms, Distribution of Income, and the Welfare of Developing Countries Manuel García-Santana ECARES Monday 25 th February, 203 Abstract I construct a tractable model to investigate the impact of
More informationIs the Distribution of Foreign Aid MDG-Sensitive?
Economic & DESA Working Paper No. 111 ST/ESA/2012/DWP/111 February 2012 Is the Distribution of Foreign Aid MDG-Sensitive? Social Affairs Degol Hailu and Raquel Tsukada Abstract This paper examines whether
More informationNBER WORKING PAPER SERIES AGING, OUTPUT PER CAPITA AND SECULAR STAGNATION. Gauti B. Eggertsson Manuel Lancastre Lawrence H.
NBER WORKING PAPER SERIES AGING, OUTPUT PER CAPITA AND SECULAR STAGNATION Gauti B. Eggertsson Manuel Lancastre Lawrence H. Summers Working Paper 24902 http://www.nber.org/papers/w24902 NATIONAL BUREAU
More informationWho Are the World s Poor? A New Profile of Global Multidimensional Poverty
Who Are the World s Poor? A New Profile of Global Multidimensional Poverty Gisela Robles Aguilar and Andy Sumner Abstract Who are the world s poor? This paper presents a new global profile of multidimensional
More informationThe Location of U.S. States Overseas Offices
The Location of U.S. States Overseas Offices Andrew J. Cassey School of Economic Sciences Washington State University October 2008 Abstract Forty U.S. states operated an overseas office in 2002. Treating
More informationNBER WORKING PAPER SERIES THE RISKY CAPITAL OF EMERGING MARKETS. Joel M. David Espen Henriksen Ina Simonovska
NBER WORKING PAPER SERIES THE RISKY CAPITAL OF EMERGING MARKETS Joel M. David Espen Henriksen Ina Simonovska Working Paper 20769 http://www.nber.org/papers/w20769 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050
More informationMarket Potential and Development
Market Potential and Development Thierry Mayer To cite this version: Thierry Mayer. Market Potential and Development. 2008. HAL Id: hal-01066164 https://hal-sciencespo.archives-ouvertes.fr/hal-01066164
More informationThe Risky Capital of Emerging Markets
The Risky Capital of Emerging Markets Joel M. David USC Espen Henriksen BI Norwegian Business School Ina Simonovska UC Davis, NBER October 30, 2015 Abstract Emerging markets exhibit (1) high average returns
More informationTechnical partner paper 1
The Rockefeller Foundation Sponsored Initiative on the Role of the Private Sector in Health Systems in Developing Countries Technical partner paper 1 Private-Public Mix in Woman and Child Health in Low-Income
More informationThe Services Trade Restrictions Database
The Services Trade Restrictions Database Ingo Borchert Batshur Gootiiz Aaditya Mattoo Development Research Group The World Bank Joint Kiel Institute World Bank Workshop on Services 23 May 2012 Motivation:
More informationPWT6 Technical Documentation
PWT6 Technical Documentation This note documents the program flows and calculations of the Penn World Table (version 6.1) and is divided into two parts. Part I is an overview of the system and Part II
More informationAPPENDIX TO ASSESSING THE EFFECT OF PUBLIC CAPITAL ON GROWTH: AN EXTENSION OF THE WORLD BANK LONG-TERM GROWTH MODEL
APPENDIX TO ASSESSING THE EFFECT OF PUBLIC CAPITAL ON GROWTH: AN EXTENSION OF THE WORLD BANK LONG-TERM GROWTH MODEL Sharmila Devadas and Steven Pennings October 28 Appendix : Comparison between the LTGM-PC
More informationHow Preferential Is Preferential Trade?
Public Disclosure Authorized Policy Research Working Paper 8446 WPS8446 Public Disclosure Authorized Public Disclosure Authorized How Preferential Is Preferential Trade? Alvaro Espitia Aaditya Mattoo Mondher
More informationThe Risky Capital of Emerging Markets
The Risky Capital of Emerging Markets Joel M. David USC Espen Henriksen UC Davis Ina Simonovska UC Davis, NBER December 31, 2015 Abstract Emerging markets exhibit (1) high expected returns to capital and
More informationLong-run Economic Growth. Part II: Sources of Growth and Productivity. Growth accounting. Today. Chris Edmond NYU Stern.
Growth accounting ong-run Economic Growth Part II: Sources of Growth and Productivity Chris Edmond NYU Stern Spring 2007 Where does growth in output per worker come from? Recall ( augmented ) production
More informationWorld Bank list of economies (February 2014)
1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania ALB Europe & Central Asia Upper middle income IBRD 3 Algeria DZA Middle East & North Africa Upper middle income IBRD 4 American Samoa ASM East
More informationVolatility, Diversification and Development in the Gulf Cooperation Council Countries 1
Volatility, Diversification and Development in the Gulf Cooperation Council Countries 1 Miklos Koren + Silvana Tenreyro 1 This draft: July 23, 2010. + Central European University and CEPR. London School
More informationNBER WORKING PAPER SERIES ASSESSING INTERNATIONAL EFFICIENCY. Jonathan Heathcote Fabrizio Perri. Working Paper
NBER WORKING PAPER SERIES ASSESSING INTERNATIONAL EFFICIENCY Jonathan Heathcote Fabrizio Perri Working Paper 18956 http://www.nber.org/papers/w18956 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts
More informationDarmstadt Discussion Papers in ECONOMICS
Darmstadt Discussion Papers in ECONOMICS Trillion Dollar Estimate: Illicit Financial Flows from Developing Countries Volker Nitsch Nr. 227 Arbeitspapiere der Volkswirtschaftlichen Fachgebiete der Technischen
More informationAssessing Fiscal Space in Sub-Saharan Africa *
Assessing Fiscal Space in Sub-Saharan Africa * César Calderón, Punam Chuhan-Pole and Yirbehogre Modeste Some The World Bank, 1818 H Street NW, Washington DC 20433, USA First Draft: October 23, 2017 Abstract
More informationDEVELOPMENT ACCOUNTING AND INTERNATIONAL TRADE
Discussion Paper No. 944 DEVELOPMENT ACCOUNTING AND INTERNATIONAL TRADE Hirokazu Ishise August 2015 The Institute of Social and Economic Research Osaka University 6-1 Mihogaoka, Ibaraki, Osaka 567-0047,
More informationEndogenous Growth Theory
Endogenous Growth Theory Lecture Notes for the winter term 2010/2011 Ingrid Ott Tim Deeken November 5th, 2010 CHAIR IN ECONOMIC POLICY KIT University of the State of Baden-Wuerttemberg and National Laboratory
More informationMeasuring Openness to Trade
Measuring Openness to Trade Michael E. Waugh New York University and NBER B. Ravikumar Federal Reserve Bank of St. Louis Arizona State University March 24, 2016 ABSTRACT In this paper we derive a new measure
More informationThe Long and Short of Empirical Evidence on the Impact of NAFTA on Canada. Eugene Beaulieu Yang Song Mustafa Zamen
The Long and Short of Empirical Evidence on the Impact of NAFTA on Canada Eugene Beaulieu Yang Song Mustafa Zamen Overview Evolution of the debate and evidence The pre-nafta world: little white lies and
More information1. Restoring the Conditions for Strong and Sustainable Growth
1. Restoring the Conditions for Strong and Sustainable Growth The sub-saharan African economic outlook remains clouded. Growth slowed sharply in 216, averaging 1.4 percent, the lowest in two decades. About
More informationFinancial Inclusion, Education & the Arab World
Financial Inclusion, Education & the Arab World Nadine Chehade nchehade@worldbank.org October 2016 Framing the discussions Why is financial inclusion important? Where does / will the Arab world stand?
More information25+ Years of Public Expenditure Reviews (PERs) What Have We Learned?
25+ Years of Public Expenditure Reviews (PERs) What Have We Learned? Institutional Matters Bill Dorotinsky, IMF June 19, 2008 Brookings Institution 1 Background Public Expenditure Reviews originated as
More informationCredit Constraints, Heterogeneous Firms, and International Trade
Credit Constraints, Heterogeneous Firms, and International Trade Review of Economic Studies 80 (2013), p.711-744. Kalina Manova University of Oxford, NBER and CEPR Links: Kalina Manova s webpage and research
More informationENABLING THE BUSINESS OF AGRICULTURE
Morocco ENABLING THE BUSINESS OF AGRICULTURE 2017 2017 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington, DC 20433; Telephone: 202-473-1000; www.worldbank.org
More informationEconomic Growth: Lecture 4, The Solow Growth Model and the Data
14.452 Economic Growth: Lecture 4, The Solow Growth Model and the Data Daron Acemoglu MIT October 30, 2014. Daron Acemoglu (MIT) Economic Growth Lecture 4 October 30, 2014. 1 / 33 Mapping the Model to
More informationSocial protection is expanding in Africa, but coverage is too low to significantly reduce inequality
Social protection is expanding in Africa, but coverage is too low to significantly reduce inequality WHAT ARE THE ECONOMIC, SOCIAL AND POLITICAL FACTORS DRIVING SOCIAL PROTECTION IN AFRICA? A high GDP
More informationChanging treaties, changing jurisprudence? The impact of treaty design differences on precedential reasoning in investment arbitration
Changing treaties, changing jurisprudence? The impact of treaty design differences on precedential reasoning in investment arbitration Wolfgang Alschner 1 DRAFT Not for citation or circulation ABSTRACT
More informationWorld Bank list of economies (January 2015)
World Bank list of economies (January 2015) (Bold indicates a change of classification) Economy Code Region Income group Lending category Other 1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania
More informationMainstreaming Aid for Trade: Where Do Cambodia and Laos Stand?
Mainstreaming Aid for Trade: Where Do Cambodia and Laos Stand? Mona Haddad Sector Manager International Trade Department World Bank Siem Reap, Cambodia May 29, 2009 Regional Meeting on Aid for Trade for
More informationKINGDOM OF SWAZILAND
December 2015 IMF Country Report No. 15/354 SELECTED ISSUES This Selected Issues paper on Kingdom of Swaziland was prepared by a staff team of the International Monetary Fund as background for the periodic
More informationEconomic Growth: Lecture 4, The Solow Growth Model and the Data
14.452 Economic Growth: Lecture 4, The Solow Growth Model and the Data Daron Acemoglu MIT November 2, 2017. Daron Acemoglu (MIT) Economic Growth Lecture 4 November 2, 2017. 1 / 34 Mapping the Model to
More informationWorld Bank list of economies (July 2016)
1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania ALB Europe & Central Asia Upper middle income IBRD 3 Algeria DZA Middle East & North Africa Upper middle income IBRD 4 American Samoa ASM East
More informationWorld Bank list of economies (June 2017)
1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania ALB Europe & Central Asia Upper middle income IBRD 3 Algeria DZA Middle East & North Africa Upper middle income IBRD 4 American Samoa ASM East
More informationWorld Bank list of economies (June 2017)
1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania ALB Europe & Central Asia Upper middle income IBRD 3 Algeria DZA Middle East & North Africa Upper middle income IBRD 4 American Samoa ASM East
More informationWorld Bank list of economies (June 2018)
1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania ALB Europe & Central Asia Upper middle income IBRD 3 Algeria DZA Middle East & North Africa Upper middle income IBRD 4 American Samoa ASM East
More informationSovereigns, Upstream Capital Flows, and Global Imbalances
Sovereigns, Upstream Capital Flows, and Global Imbalances Laura Alfaro Şebnem Kalemli-Özcan Vadym Volosovych Harvard University, NBER Koc University, Harvard University, NBER, and CEPR Erasmus University
More informationWorld Bank list of economies (June 2018)
1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania ALB Europe & Central Asia Upper middle income IBRD 3 Algeria DZA Middle East & North Africa Upper middle income IBRD 4 American Samoa ASM East
More informationAssessing Aid and the Collier/Dollar Poverty Efficient Aid Allocations: A Critique
Assessing Aid and the Collier/Dollar Poverty Efficient Aid Allocations: A Critique Jonathan Beynon Department For International Development London, UK Economic Policy and Research Department: Discussion
More informationTrade Without Scale Effects
Trade Without Scale Effects Pedro Bento Texas A&M University May 2018 Abstract Across countries and over time, average incomes are related to population density, but not population keeping density fixed).
More informationMacroeconomic Effects of Financial Integration, Demographic Aging and Automation Technology
Macroeconomic Effects of Financial Integration, Demographic Aging and Automation Technology Inaugural-Dissertation zur Erlangung des Grades eines Doktors der Wirtschafts- und Gesellschaftswissenschaften
More informationPrologue Acemoglu et al. (2001) Banerjee et al. (2002) Lin (1992) Epilogue. Property Rights. Dr. Kumar Aniket
Property Rights EC307 ECONOMIC DEVELOPMENT Dr. Kumar Aniket University of Cambridge & LSE Summer School Lecture 3 created on June 6, 2010 READINGS Tables and figures in this lecture are taken from: Chapters
More informationWorld Bank list of economies (April 2012)
1 Afghanistan AFG South Asia Low income IDA HIPC 2 Albania ALB Europe & Central Asia Upper middle income IBRD 3 Algeria DZA Middle East & North Africa Upper middle income IBRD 4 American Samoa ASM East
More informationJUNE (Includes Djibouti and Yemen)
98118 JUNE 2015 (Includes Djibouti and Yemen) Acknowledgments This report was prepared by a team led by Punam Chuhan-Pole and comprising Vijdan Korman, Mapi M. Buitano, and Beatrice A. Berman. Paul Breton,
More information