Distortion of agricultural incentives in East Africa: effects on agricultural value added

Abstract

This study examines the effects of distortion of agricultural price incentives on agricultural value added in East Africa. The World Bank, IFPRI, FAO, and CSP are the sources of data. The dataset ranges from 1981 to 2018, and the error-corrected LSDV model is used to analyze the data. The results indicate that agricultural price incentives have positive and significant effects on agricultural value-added. Aggregate nominal assistance coefficient, exportable agricultural products nominal assistance coefficient, and nominal rate of protection have increased agricultural value-added significantly. Agricultural price incentives targeting different levels of value addition have larger effects than those targeting aggregate outputs. This implies that agricultural incentive policies and market conditions in support of local producers are vital to enhancing AVA in East Africa. Besides, larger areas of arable land, lower agricultural employment, a smaller population size, a larger GDP, less spending on education, and a better-performing polity contribute to a significant increase in the regional agricultural value added. The results generally imply that agricultural price incentives are vital to accelerating agricultural value addition in East Africa. Governments in this region should thus consider revising agricultural policies in a pro-agricultural way to further accelerate regional growth in agricultural value-added. Enhancing agricultural price support needs to be a crucial element of policy revisions in the region.

Impact Statement

In East Africa, agriculture is the main source of employment for a large section of the population. However, agricultural incentives have been reportedly distorted against agriculture, and sectoral income has been low. Consequently, farmers’ income from agricultural value addition has been low. This study reports the effects of the distortion of agricultural incentives on agricultural value added in East Africa. The study shows that favorable agricultural incentives enhance agricultural value-added. The findings have strong implications for the region’s smallholders, who are the subject of heavy taxation, either directly or indirectly. It will have far-reaching consequences for the poor, who rely on agriculture for a living. In particular, the findings influence regional anti-agricultural policy design, which is vital for the regional goal of achieving inclusive growth and structural transformation.

Keywords:

• Agricultural protection
• price incentives
• price distortion
• NAC
• NRP
• LSDVC

REVIEWING EDITOR:

• Aye Goodness, University of Agriculture, Benue, Nigeria

SUBJECTS:

• Development Studies
• Development Policy
• Politics & Development

Authors’ contributions

Conceptualization, data collection, formal analysis, and writing the original draft were all undertaken by the first author. The second and third authors supervised this work, revised and engaged in providing intellectutal support. All authors have read and agreed to the submitted version of the manuscript for publication. All authors agree to be accountable for all aspects of this work.

Disclosure statement

The authors report there are no competing interests to declare.

Data availability statement

The employed dataset is publicly available. The NRA and Pop_Agric, are retrieved from the World Bank datasheet at: www.worldbank.org/agdistortions. The NRP is retrieved from the IFPRI datasheet at: www.agincentives.org/nominal-rate-of-protection. The AVA, Educ, GFCF, and Pop_Total, are retrived from the World Bank datasheet at: https://databank.worldbank.org/. The Land, AgEmp, and GDP, are obtained from the FAO datasheet at: www.fao.org/faostat/en/. Polity data is retrieved from the CSP datasheet at: www.systemicpeace.org/inscrdata.html.

Notes

1 We compute exportable agricultural products NAC following similar procedures for agreggating NAC. That is: NAC_Exportable = NRA_Exportable +1.

2 A normalized polity data is used for the employed models to cease. The transformed series falls between two extreme values of 0 and 1. Both minimum (min) and maximum (max) values were theoretical and computed as follows:$\mathit{\text{Polity}}=({\mathit{\text{Actual Polity}}}_{\mathit{\text{it}}}-{\mathrm{\text{min}} \mathit{\text{Polity}}}_{\mathit{\text{it}}})/({\mathrm{\text{max}} \mathit{\text{Polity}}}_{\mathit{\text{it}}}-{\mathrm{\text{min}} \mathit{\text{Polity}}}_{\mathit{\text{it}}}).$

3 The NAC_Total coefficient is recalculated accounting for log-transformed AVA. We exponentiate the coefficient, subtract 1 and multiply by 100 to find % change. That is: exp ((0.102)-1)*100 % = 10.74%.

4 Similarly, we interpret the coefficient of NAC_Exportable as: exp ((0.089)-1)*100% = 9.31%.

5 The coefficient of NRP is: exp ((0.026)-1)*100% = 2.63%.

Additional information

Funding

This study was financed by Jimma University.

Notes on contributors

Biru Gelgo Dube

Biru Gelgo Dube is a PhD candidate at Jimma University. He is interested in researches addressing political economy, agricultural policies, institutions, and agricultural technology adoption.

Adeba Gemechu Gobena

Adeba Gemechu Gobena is an associate professor of Agricultural Economics in the Department of Agricultural Economics and Agribusiness Management at Jimma University, Ethiopia. He has ample experiences on micro-economic and macro-economic researches. Specifically, he is more interested in researches addressing natural resource economics and development economics including agricultural policies, institutional economics, agricultural technology adoption, agricultural marketing, climate smart agriculture, and agricultural finances among money others.

Amsalu Bedemo Beyene

Amsalu Bedemo Beyene is an associate professor of economics at the Department of Policy Studies, Ethiopian Civil Service University (ECSU). The areas of his research interest include macroeconomic analysis, governance, institutions, and economic growth/development, political economy of financial development, agricultural development and structural transformation in Ethiopia, poverty, income inequality, and growth.