PUBLICATIONS

@unpublished{Asongu_424,
author = {Simplice Asongu & Voxi Amavilah A John Ssozi},
url = {http://www.afridev.org/RePEc/agd/agd-wpaper/Is-Aid-for-Agriculture-Effective-in-Sub-Saharan-Africa.pdf},
year = {2017},
date = {2017-09-08},
abstract = {One of the key economic development challenges facing Sub-Saharan Africa (SSA) is its low agricultural productivity. Governments, donors, and foreign investors have underinvested in African agriculture even though research evidence shows that higher agricultural productivity would boost economic growth and poverty reduction. Solutions to the problem require a number of interconnected strategies, including, but not limited to, research on seeds and inputs, extension services, rural development, credit, institutional, and trade and price stabilization policies. We use the system two-step Generalized Method of Moments to examine whether official development assistance (ODA) for agriculture and rural development is helping to boost agricultural productivity. We find a positive relationship between ODA and agricultural productivity. However, when broken down into the main agricultural ODA recipient sectors, there is a substitution effect between food crop production and industrial crop production. While there exists a positive relationship between ODA for industrial and export crops output per worker (agricultural productivity), ODA for food crops has a negative relationship. Better public institutions and economic freedom are also found to enable agricultural productivity growth and to increase the ODA effectiveness. We correct the results for spurious correlation assuming that more ODA might be allocated where agricultural productivity is already increasing due to some other factors. Concerning the determinants of ODA allocation, we find that the allocation of ODA for agriculture is primarily determined by agricultural need, and that the expected effectiveness increases the ODA receipts. Finally, there is a weak ODA-led structural economic change effect in SSA. Labor released from agriculture to the urban sector(s) has a positive market effect on agriculture but is not engendering significant structural economic transformation.},
keywords = {Foreign aid; Agriculture; Development; Africa},
pubstate = {published},
tppubtype = {unpublished}
}

@unpublished{Asongu_427,
author = {& Nwachuwku J C Asongu S. A.},
url = {http://www.afridev.org/RePEc/agd/agd-wpaper/Quality-of-Growth-Empirics.Comparative-Gaps-Benchmarking-and-Policy-Syndromes.pdf},
year = {2017},
date = {2017-09-01},
abstract = {This study uses a new dataset to provide comparative gaps, benchmarking with best performers and policy syndromes of growth quality in 93 developing countries with data for the period 1990-2011. Sigma and Beta estimation strategies are used to provide between and within cross-country dispersions. The empirical evidence is based on: time, regions, income levels, resource-wealth, state fragility and time-consistent growth quality (GQ) performance. First, for ‘within dispersions’ the following outcomes are established: (1) GQ dispersions within fundamental characteristics have been decreasing over time, (2) From a time-dynamic view, countries within Asia and the Pacific have experienced the highest reduction in GQ differences while nations in the Middle East and North Africa (Central and Eastern European) region have witnessed the highest (lowest) differences, (3) From an income perspective, upper-middle-income (Low-income) countries have the lowest (highest) differences in GQ. (4) Resource-rich and Non-fragile countries have higher differences relative to their Resource-poor and Fragile counterparts respectively. Second, for ‘between dispersions’ and policy syndromes, we found two time-consistent extremities. (1) In decreasing need of policy intervention, the following are apparent for the Policy syndrome extreme: Hopeful, Fragile, Sub-Saharan African, Low-income and Resource-rich countries. (2) In the same line of policy inference, the following are apparent for the Syndrome-free extreme: Central and Eastern European, Asia and the Pacific, Latin American, Best Performing and Upper-middle-income countries. Their predispositions are clarified and policy implications discussed.},
keywords = {Quality of growth; Development; Catch-up},
pubstate = {published},
tppubtype = {unpublished}
}