Amity Journal of Management Amity Business School

Vol. VI, No. 2, July - December 2018 Amity University, Madhya Pradesh (ISSN 2347 – 1832)

DETERMINANTS OF MANUFACTURING SECTOR GROWTH IN ETHIOPIA

Dr. Manoj Kumar Mishra1

ABSTRACT

Over the last two decades the Ethiopian manufacturing sector has experienced rapid expansion in terms
of the number of foreign direct investment, sales, and employment creation. This paper examines the
determinants of the manufacturing sector growth using aggregate data compiled by the Central
Statistical Agency (CSA) of Ethiopia. To achieve the objective of the study we used the secondary data
and analyzed it using descriptive (percentage, mean, standard deviation) statistics of SPSS analysis. To
date, there has been little attention given to how manufacturing sector growth relates to other equally
important variables such as manufacturing value added, inflation, and manufacturing export per capita
in the country. This study explored the explanatory power of the independent variables of FDI,
manufacturing value added, inflation, permanent employment, and manufacturing export per capita. We
have used secondary data for this study collected from National Bank of Ethiopia, “World Bank” &
Ministry of Finance & Economic Development from 2007/08 to 2016/17. This study shows that the
independent variables of manufacturing value added, manufacturing export per capita and inflation were
not statistically significant in explaining manufacturing sector growth (dependent variable).
The independent variables FDI net flow and permanent employment were statistically significant in
explaining manufacturing sector growth (dependent variable).

Keywords: Manufacturing sector, FDI, Per capita income, Economic growth etc.

INTRODUCTION from agriculture to manufacturing,

economies of scale and positive spillovers
Manufacturing is defined as physical or
effects and create broad based job
chemical transformation of material
opportunity and improve the total factor
components into new products (ISIC Rev, 4,
productivity and competitiveness of the
2008). The definition also includes the
overall economy are also the other
assembly of component parts of
advantages of manufacturing. Success
manufactured products as a manufacturing
experiences of developed countries show
activity whether the production is done at
that manufacturing is the pillar behind a
factory or home, sold at retail or wholesale,
sustained growth.
and whether power driven machine is used
or not. According to Narasimha and According to the “Central Statistical
Ramesh, manufacturing is the engine of Authority” there were 1,930 large- and
economic growth and structural medium-scale, 43,338 small-scale, and
transformation. Ethiopia is one of the few 974,676 cottage/handicraft establishments
African countries that have formulated and during 2007/08 (CSA, 2003). The majority
implemented a full-fledged industrial of the establishments do not use power-
development strategy since early 2000s driven machinery, irrespective of the
when industrial policy had been a taboo in number of persons employed. The sectoral
the international policy forums. The growth structure of the manufacturing sub-sector,
of the manufacturing sector within industry 2007/08 based on numbers of
is essential to build national technological establishments, reveals that food and
capacity, industrial capability, technology beverage establishments accounted for 52%
progress, productivity and capital of the total manufacturing enterprises,
accumulation. Transfer of surplus resources while textiles accounted for 22%, Ethiopia
has experienced rapid economic growth
1 Associate Professor in Economics, Ethiopian since 2005 with real Gross Domestic
Civil Service University Addis Ababa, Products (GDP) growth rate of 10.5 percent
Africa per annum compared to 5 percent for Sub-

1
Saharan Africa between 2005 to 2014 ,This 2012). No over emphasis of the role of
rapid economic growth particularly for an manufacturing sector in development of
economy without oil, gas or any significant any economy was also discussed (Szirmai,
minerals and much ahead of many notable 2009) argued about the empirical
countries with oil. correlation between per capita income and
degree of industrialization of any
During the global economic recession of
developing countries. (Tybot, 2000)
1980s, a very low industrial growth was
discussed manufacturing sector as a growth
noticed and it was due to the declining oil
engine, a key source of creating skilled jobs
prices. To address this problem of low
and avenue of spillovers to other sectors.
growth, Govt. introduced many adjustment
(Mallik, 2008) focused on limited foreign
reforms, but these reforms were not much
inflows for developmental purposes which
successful. Though decades old debate on
limits the growth of manufacturing sector,
the relationship between economic growth
which ultimately results as hindrance of the
and the manufacturing sectors was not
capability of developing countries to invest
stopped but on the other side there was no
in growth projects eg projects for
any evidence found to “show how
infrastructure, education, energy,
manufacturing sector varied relative to the
communications and roads.
components of economic development such
as FDI(Foreign Direct Investment), labour Other research scholars (Chudnovsky &
cost, inflation and manufacturing value Lopez, 2002; Dunning, 2002) discussed
added services.” Number of existing about FDI as investment tool for
studies on manufacturing sector and FDI is stimulating growth in the manufacturing
not high but produced mixed results, sector and other vital sectors within an
existence of knowledge gaps are confirmed economy. There has been a little evidence to
by it. Despite of the fact that manufacturing show the varied relationship between
sector has an important role the in economy growth of manufacturing sector and other
of any country, and not only manufacturing important non-economic and financial
sector but the sensitivity of the variables of variables. This study addressed how other
inflation, labour costs, and manufacturing variables relate to manufacturing sector
value added also have important role to growth in Ethiopia. Exploring the
play in economy of any country; there are explanatory power of these variables will
less number of comparative study found fill the knowledge vacuum that currently
which can show the relationship between exists in the study of manufacturing sector
growth of manufacturing sector and growth in country.
inflation, labour cost, Foreign Direct
Statement of the Problem
investment and Manufacturing value
added in Ethiopia. Manufacturing sector play significant role
in the creation of employment
Although ,there exists many empirical opportunities and generation of income for
studies suggesting a significant relationship quite a large proportion of population.
between manufacturing sector and FDI and Mead (1998) observes that the health of
GDP(Quattara, 2004) and (Fedrick, 2000),
economy as a whole has strong relationship
few other studies examines the relationship
with the health and nature of
between manufacturing „sector growth and
manufacturing sectors. Manufacturing
explanatory variables, eg labor costs,
sector is a significant role for economic
inflation, FDI, and manufacturing value
growth in money developing countries
added in Ethiopia. „The transformation
worldwide, including Ethiopia. Since the
from a traditional economy into modern
manufacturing sector is very important to
economy where technology and modern the growth of economy, knowledge of its
production activities in manufacturing relationship with the macroeconomic
assume a significant role has remained a
determinant present in its economic
defining characteristic of economic growth environment is crucial.
and development (Naude and Szirami,

2
Literature recognizes that determinants 2. To identifying the major challenges and
factors influence the performance of opportunities of the manufacturing
manufacturing sector growth. Though there sector in Ethiopia and to suggest some
are empirical studies that highlight factors intervention measures.
affecting the performance of manufacturing
Significance of the Study
sectors, there is little work that combines
both internal and external environmental The significance of this study shows how
factors. On the other hand, other studies manufacturing sector interacts with the
(Opler and Titman, 1994) suggest that firm determinants of its growth. And also, it is
specific (internal) factors seem to be the important to know how the determinants
major determinants of the manufacturing affect the growth of the manufacturing
sectors. sector and to give decision for the sector
what policies make to improve the
Manufacturing industries have to play an
performance of growth in the future.
important role in terms of contributing to
the reduction of unemployment and to LITERATURE REVIEW
better the standard of living of the people of The manufacturing sector plays the most
Ethiopia. This study seeks to find out the important and dynamic role in the
determinants of manufacturing sectors industrialization process. The available
growth in Ethiopia. The significant role of evidence indicates that about 25% of the
manufacturing industries in the “Ethiopian GDP should come from the industrial
economy suggests that an understanding of sector. 17.4 % of the industrial output
their performance is crucial to the stability should originate from the manufacturing
and health of the economy”. sector and 10% of the population should be
Research Questions employed in the industrial sector. The
largest industrial sector, and manufacturing
Accordingly, this study aims to address the
within it, grew much faster after 2005.
following research questions.
“Manufacturing can be classified into
What are the major determinants that affect different categories by using different
the growth of the manufacturing sectors in criteria. According to the Central Statistical
Ethiopia? Authority (CSA)”, the Ethiopian
Which determinant has the greatest manufacturing sector is classified into three,
influence on manufacturing sector growth namely large- and medium-scale, small-
in Ethiopia? scale and cottage/handcraft manufacturing.
This categorization is mainly based on the
Objective of the Study number of people employed and use or
The objective of the research is to identify non-use of power-driven machinery: Large-
factors that determine the growth of and medium-scale manufacturing
manufacturing sector in Ethiopia and it will establishments use power-driven
be designed to achieve the following machinery and employ 10 persons and
general and specific objective. above. Small-scale industries are those
establishments that employ less than 10
General Objective persons and use power-driven machinery.
The general objective of this study is to Manufacturing sector contributed a
determine the determinants of significant proportion of the total value
manufacturing sector growth in Ethiopia added, followed by cottage/handicrafts.
and to recommend alternative solution. This suggests that we should have a closer
Specific Objective look at the performance of large- and
medium-scale manufacturing
1. To demonstrate the determinants of the
establishments. The Ethiopian large and
manufacturing sector growth in the
medium-scale manufacturing sub-sector is
economic transformation process in
characterized by the dominance of four-
Ethiopia.

3
consumer good producing industrial still there is wide range of opportunities
groups, namely the food and beverages, amidst the challenges in developing the
textiles, leather and leather articles groups. manufacturing sector. The government has
These groups of industries account for the been attempting to overcome the challenges
bulk of the gross value of output and for facing the sector and exploit the
the value added of the sub-sector. opportunities to expand and diversify the
manufacturing industries and their
Opportunities and Challenges in the
Manufacturing Sector products. The idea of developing
comprehensive manufacturing industry
Although manufacturing industries was started post 1991. The appropriate
producing clothes, ceramics, machine tools, government policies and strategies is one
and leather products began in 1957, it never of the opportunities that helped Ethiopia to
developed well until the overthrow of the develop the manufacturing sector. The
military rule because the sector was policies and strategies carried out by the
obstructed by lack of infrastructure, scarcity government encouraged the establishment
of private and public investment as well as of various private manufacturing
lack of appropriate policies, contributed to enterprises having reversed the command
the insignificance performance of the economic system installed by the previous
manufacture sector pre-1991. “Cognizant of government. In fact, the Ethiopian
the importance of the manufacturing sector government managed to reverse the
for economic, revenue generation command economic system in the country
and employment, the government has through fostering competition, opening free
designed various policies and strategies to market economy and promoting the private
develop it.” Considering internal, regional, sector. Besides, the government was
continental and international situations into devoted in liberalizing the foreign exchange
account, Industrial policies were designed market, rationalize public expenditure,
and implemented at different times in a bid introducing new investment codes and
to create not only as many job removing export tax refund in its attempt to
opportunities to the youth as possible but develop the manufacturing sector. The
also to facilitate the progress of the entire 1994/95 – 1996/97 economic reform
Industrial development. In this regard, program was encouraging and promoting
different international organizations and potential private investors to participate in
media have persistently commending the the manufacturing sector. These efforts
boosting manufacturing sector in Ethiopia. have contributed to the enhancement of
International organizations like World broad-based economic growth in the
Bank and the International Monetary Fund country in general and the manufacturing
reported the booming manufacture in sector in particular.
Ethiopia every year. CNN, BBC, The
economist, The Financial Times and Quartz According to Ministry of Finance and
are some among many international Economic Development (MoFED), the
organizations that have reported about this manufacturing value added well
progress recently. Quartz emphasized the progressed in 1993. However, that
role of the manufacturing sector to the remarkable growth of the manufacturing
development of the country. “It reported sector has started to slow down to average
that the sector has been playing an value added annual growth of 3 per cent
encouraging role particularly in the past in 1996-2003. Following the slowdown,
two years of the second Growth and the government adopted an export
Transformation Plan. “ In doing so, the promotion strategy focusing on
government managed to provide a lot of job diversifying and maximizing the
opportunities to its citizens in the manufacturing products. Cognizant of such
manufacturing sector. In fact, the fast encouraging move towards improving the
sustainable economic development industrial sector, the government has
achieved so far could be appreciated but consolidated its industrial policy and

4
strategy in 2002/03, mainly focusing on Global Competitiveness Index 2014 and
the manufacturing sector development in 2015, the measure constraints in developing
an integrated manner with the smallholder the manufacturing sector includes
farming. One of the approaches the inefficient government bureaucracy, foreign
government has been utilizing to develop currency regulations, access to finance,
the manufacturing sector was integrating it corruption, and inadequate supply of
with the agricultural sector. This was infrastructure. Rent collection and corrupt
mainly implemented in the first Growth practices, inflation, lack of peace and
and Transformation Plan. In due process, stability could also be other mounting
the government has developed and created challenges that could jeopardize the
a conducive environment for the private manufacturing sector in particular and the
sector. As a result, the participation of entire development schemes of the country
potential investors in the manufacturing in general. These challenges could severely
sector has begun to grow from time to time affect the execution of the development
due to the various incentives set by the targets set in the second Growth and
government. These incentives encourage Transformation Plan within the remaining
productivity particularly in the textile three consecutive years. In conclusion, the
industry that has performed well in the past manufacturing sector in Ethiopia has been
two years of the second Growth and enjoying some opportunities amidst a
Transformation Plan. According to the number of perplexing challenges retarding
Central Statistics Agency, the their development. The government of
manufacturing sector grew by 11.9 percent Ethiopia, since the coming of the Ethiopian
and contributed to the Gross Domestic People‟s Revolutionary Democratic Front
product 36 percent. It is also crystal clear (EPRDF) in to power in 1991, has been
that the large and medium manufacturing exerting a tremendous effort so as to
sectors have got a special attention through upgrade the expansion, diversification and
the industrial park developments in productivity of the manufacturing sector.
different parts of the country. This is Having recognized its benefit to the overall
another opportunity for the sector to development of the country and its
develop its productivity and contribution to job creation, the
competitiveness. The expansion of government has been exerting tremendous
Industrial parks coupled with the efforts to develop it (By Tesfaye Lemma).
previously established industrial zones
The manufacturing sector can spur
could play a remarkable role in promoting
economic growth and development because
the manufacturing sector making easy to
of its immense potential for employment.
both public and private investments.
However, it needs still to withstand the
The incentives and government support to available obstructions that could retard the
those private investors who have been forward move. The manufacturing sector of
investing on the manufacturing sector Ethiopia is in its infant stage due to many
could also be considered as another interrelated problems. These problems are
opportunity in enhancing the sector. generally related to finance, technology,
According to Export Trade Duty Incentive market, policy, input supply and other
Scheme Establishing Proclamation No. socio-economic factors.
249/2001, the government provides various
Determinants of Manufacturing Sector
investment incentive packages including Growth in Ethiopia
exemption from income tax and payment of
custom duty. Irrespective of all these Most of the literature shows that the
aforementioned opportunities, there lies a determinants of manufacturing sector
number of perplexing challenges growth are foreign direct investment,
obstructing both the diversification and saving rate, exports of product,
productivity of the manufacturing sector. employment creation and value added
According to World Economic Forum‟s manufacturing. Many of the other

5
determinants that could advance the improvements in the performance of the
growth of the countries, the contribution of manufacturing sector.
manufacturing sector growth are one of the
main concerns in our study. Therefore, the
determinants that will affect the growth of
manufacturing sector are our main focus
area.
Production and Value Addition of the
Manufacturing Sector in Ethiopia
In most literature review one determinants
of manufacturing sector growth is gross
value of manufacturing industries. Another Figure 1: Manufacturing value added
indicator of the performance of the
Source: World Bank
manufacturing sector is the value added
per person, defined as the ratio of value Manufacturing, value added (% of GDP) in
added created to the number of persons Ethiopia was reported at 4.3421 % in 2016,
employed. Value added per person is also according to the World Bank collection of
known as labor productivity. Value added development indicators, compiled from
per person declined at an annual average officially recognized sources.
rate of 3.4% during the 1980s. This might Manufacturing refers to industries
have been be due to, among other things, belonging to ISIC divisions 15-37. Value
redundancy of labor in the sector together added is the net output of a sector after
with obsolete and outdated technology adding up all outputs and subtracting
causing the marginal product of labor to intermediate inputs. It is calculated without
decline over time. After the reform, making deductions for depreciation of
however, value added per person fabricated assets or depletion and
increased. Labor productivity was highest degradation of natural resources. The origin
in metal, followed by those of food and of value added is determined by the
leather and shoes. Labor productivity International Standard Industrial
registered an annual average growth rate of Classification (ISIC), revision 3. Note: For
33.9%, 30.1%, and 25.6% in the metal, food, VAB countries, gross value added at factor
and leather and shoe industrial groups, cost is used as the denominator.
respectively, during the 1991/92 - 1998/99 Manufacturing and Job Creation in
period. Ethiopia
The manufacturing sector has shown The actual level of manufacturing activity
improvements in terms of gross value of and its employment creation was very low
output, value added, and value added compared with the case in other developing
per person during the post-reform countries. Manufacturing sub-sector, in
period. This might be attributed to the particular, serves as important sources of
incentive for profit and the creation of a employment, especially for the rapidly
relatively conducive environment growing urban population in Ethiopia
induced by the granting of managerial Employment creation in manufacturing
autonomy to public enterprises; the industries is another determinant in the
active involvement of a number of growth of the sector. In Ethiopia the
private manufacturing establishments; proportion of labor productivity growth in
the improved availability of inputs and service sector is relatively high than
spare parts; and the recovery of the manufacturing sector.
agricultural sector, which enhanced the
supply of raw materials to the
manufacturing sector. These factors are
expected to continue to contribute to the

6
METHODOLOGY OF THE STUDY in preceding sections of the report. The
purpose of this study is to assess the
Data Collection determinants of manufacturing sector
We use secondary data for this study growth in Ethiopia. The study has
collected from National bank of Ethiopia, employed SPSS and Microsoft-excel in
World Bank & ministry of finance economy analyzing the collected data. Percentage,
development from 2007/08 to 2016/17. mean and standard deviation have been
Manufacturing sector, FDI, permanent used to analyses the row data and we
employment, manufacturing export per analyze the data by using multiple
capita, inflation and manufacturing value regression to know the significant effect of
added were retrieved from the World Bank the manufacturing sector determinate.
Development Indicators. We operationalize Table 1 : Growth Rate
the variables as follows: Manufacturing
sector growth is defined as a percentage of Manufa Mining and Electricity Constr
GDP from 2007/08 to 2016/17. A FDI net cturing Quarrying and Water uction
inflow is defined as a percentage of GDP 16.9 6.3 10 38.2
16.6 -3.2 6.8 23.9
from 2007/08 to 2016/17. Inflation is
18.2 -25.6 4.5 31.6
defined as the annual percent change in
18.4 -3.3 15 25
consumer prices from 2007/08 to 2016/17.
17.4 -29.8 11.4 20.7
Methods of Data Analysis
The data collected from the survey will be
tallied, systematically organized, tabulated
and summarized in items based on tables
and charts. The study will also employ
SPSS and Microsoft-excel to analyze the
collected data. In this study, since
independent variables are five we use a
multiple regression and descriptive
statistics to analyze the data gathered from
different data sources. Descriptive statistics
such as percentage mean and tables were
the tools used to summarize and analyze
the data. In addition, analysis of variance Figure 2 : Growth Rate
(ANOVA) was used to test the hypotheses Source: National Planning Commission
stated because analysis of variance
(ANOVA) was used to determine whether
there are any significance differences
between the means of two or more Table 2: Growth Rate
independent groups. Fiscal Manu- Mining and Electricity Cons-
Variables of the study year facturing Quarrying and Water truction
2012-13 33.6 11 8.3 47.1
Dependent variable: Manufacturing sector
growth 2013-14 33.4 9.1 7.6 49.9
Independent variables: FDI net flow, 2014-15 33 5.7 6.6 54.8
permanent employment, inflation,
manufacturing export per capita and 2015-16 32.4 4.5 6.3 56.8
manufacturing value added.
2016-17 25 1.1 3 70.9
DATA ANALYSIS AND DISCUSSION
This section discusses the results of the
study based on the research tools presented

7
 get the minimum adjusted value of Good
Fit(GoF), which is 0.941(Wetzels,
Odekerken-Schröder, & Van Oppen, 2009).

0.974 is the GoF value in this study

(Wetzels, Odekerken-Schröder, & Van
Oppen, 2009), showing model as a good fit
compared to the specified minimum. The
structural relations and hypothesis testing
were validated.

The theory is examined underlying the

Figure 3: Share in Industry field, the relationships between
Source: National Planning Commission manufacturing sector growth and FDI,
inflation, manufacturing value added,
From the above figure/table the manufacturing export per capita and,
manufacturing sector increased by 17.4 permanent employment by using multiple
percent and constituted about 25 percent of regression models.
industrial sector. Construction industry, on
the other hand, contributed more than half The regression equation is comprised of the
(70.9 percent) to industrial sector and various variables:
expanded by 20.7 percent signifying the
Y= β0+β1X1+β2X2+β3X3+β4X4+β5X5+ε---- (1)
leading role the construction sector plays in
terms of roads, railways, dams and Where,
residential houses expansion. Electricity &
water and mining & quarrying had 3 and α = intercept,
1.1 percent contribution to industrial
production, respectively. Y = dependent variable, manufacturing
growth sector (which was predicted or
From the model summary table below of explained)
SPSS output, the effect of the relationship
was identified based on the R statistic, β0, β1, β2, β3, β4 and β5 : coefficient of X,
which in a variable regression is the same (slope of regression line, measures how
as the correlation coefficient. In this case the much of Y varies relative to changes in the
R is 0.987 indicating strong relationship. independent variables).

The proportion of variance in the X1, : independent variables of permanent

dependent variable which is accounted by employment
the independent variables, is explained by
X2, : manufacturing value added
the R Square Statistics.
X3,: FDI net flow
In this case the model accounts for 97.4% of
the variance in the dependent variable, X4 : manufacturing export per capita and
manufacturing sector growth. The adjusted
R square is higher, indicating 94.1% of the X5 : inflation
variance is accounted for by the model.
With respect to the fitness of the model, the These values, predict or explain the value of
coefficient of determination (R2) for the Y, the manufacturing sector growth. ε -
manufacturing sector growth was 97.4%. Error term used for predicting the value of
Y, with a given value of X. We developed
The R square value was substituted , the following hypotheses for this study:
suggested by Cohen (1977), and the value of
Commonality established by Fornell and Hypothesis 1 H01: The “permanent
Larcker(1981), for validity testing we can employment” is not accountable for

8
significant variation in manufacturing manufacturing export per capita (M=2.9,
sector growth. SD=0.89).

Ha1: The “permanent employment” is Given the foregoing coefficients the

accountable for a significant variation in following are the recalls of the research
manufacturing sector growth. questions for the study, together with the
null and alternative hypotheses and the
Hypothesis 2 H02: The “manufacturing results of the research question. Next is the
value added “is not accountable for a general form of the regression equation that
significant variation in manufacturing explains how variations in the independent
sector growth. variables explain manufacturing sector
growth in Ethiopia.
Ha2: The manufacturing value added is
accountable for a significant variation in the Manufacturing sector growth = -132.874+
manufacturing sector. 0.005*(employment) - 21.383*(value added)
+ 24.609*(FDI) – 14.218*(export per capita) +
Hypothesis 3 H03: The “inflow of foreign
0.012*(inflation). The p-value shows
direct investment” is not accountable for a
whether the variation in the dependent
significant variation in manufacturing
variable (manufacturing sector growth)
sector growth.
explained by the independent variable is
Ha3: The “inflow of foreign direct significant or not. If the p-value is greater
investments” is accountable for a significant than 0.05, the null hypothesis would not be
variation in manufacturing sector growth. rejected. The p-value of the data is greater
than 0.05, for the coefficients or the
Hypothesis 4 H04: The “manufacturing independent variables of manufacturing
export per capita” is not accountable for value added manufacturing export per
significant variation in manufacturing capita and inflation the null hypotheses
sector growth. were not rejected. This implied that the
variations in the independent variables
Ha4: The “manufacturing export per (coefficients) were not statistically
capita” is accountable for a significant significant in explaining manufacturing
variation in the manufacturing sector. sector growth (dependent variable). The p-
Hypothesis 5 H05: The “rate of inflation” is value of the data is less than 0.05, for the
not accountable for a significant variation in coefficients or the independent variables
manufacturing sector growth. FDI net flow and permanent employment
the null hypotheses were rejected. This
Ha5: The “rate of inflation “is accountable implied that the variations in the
for a significant variation in manufacturing independent variables (coefficients) were
sector growth. statistically significant in explaining
manufacturing sector growth (dependent
RESULT AND DISCUSSION variable).

Table 8 shows the descriptive statistics for CONCLUSION AND SUGGESTION

the dependent and independent variables.
List for the results of regression analysis are Two fundamental questions related to the
given in Table 5 of Appendix. relationship between the manufacturing
growth, FDI, per capita manufacturing
With the dependent variable had a mean export, inflation, permanent employment
average of 62 and SD = 34.6, and the and manufacturing value added in Ethopia
independent variables of permanent from the year 2007-2008 and from the year
employment (M=3727.1 SD 2819.1) and FDI 2016-2017 was sought in the study.
(M= 2.1, SD= 1.71) and manufacturing
value added (M=4.14, SD=0.62) inflation The first research question focused the
rate (M= 16.8, SD= 13.02) and relationship between manufacturing sector

9
growth and FDI, manufacturing export per Sokunle, R.O & Harper, A.(2016). The
capita, inflation, permanent employment determinants of manufacturing sector
and manufacturing value added in Ethiopia growth in Sub-Saharan African countries.
from the year 2007-2008 and from the year Research in Business and Economics
2016- 2017. Statistical analysis was done Journal,12,pp1-9.
through Multiple regression and no
significant relationship between Fisher, S. (1991). Growth, macroeconomics
manufacturing sector growth and the and development. NBER Working
independent variables manufacturing Paper,Cambridge, M.A.
export per capita, inflation, and
Ghura, D., & Goodwin, B. (2000).
manufacturing value added was found. It
Determinants of private investment: A cross
was found that there is a significant
regional empirical Investigation.
relationship between “Permanent
Applied Economics, 32(14), 1819-1829.
employment” and FDI and Manufacturing
Retrieved from
sector growth in Ethopia from year 2007-
http://www.ingentaconnect.com/content/
2008 and from year 2016-201.It implies that
routledg/raef
the main determinants of manufacturing
sector growth are “F.D.I.” and “permanent African Development Bank Group. 2016.
employment”. This study added the value "Federal Democratic Republic of Ethiopia
to the previous researches which focus on Country Strategy Report 2016-2020."
the relationship between FDI, Permanent https://www.afdb.org/fileadmin/uploads
employment and growth of manufacturing /afdb/Documents/Project-
sector. andOperations/ETHIOPIA_CSP_BPPS_EN.
pdf
REFERENCES
Fredrick, M. (2000). Determinants and Ethiopia‟s Manufacturing Industry
constraints to private investment: The case Opportunities, Challenges and Way
of Kenya. African Institute for Economic Forward: A Sectoral Overview by Tekeba
Development and Planning (IDEP). Eshetie

Fry, M. (1980). Saving, investment and the The Structure and Performance of the
cost of financial repression. World Ethiopian Manufacturing Sector Working
Development, 8, (731-750). doi: Paper Series :Arkebe Oqubay
10.1016/0305-750X (80)90030-3

10
APPENDIX
Table 3 : Share of Manufacturing

GDP per Share of manufacturing Share of Industry Manufactured

capita value added in GDP value added in GDP exports per capita
2000 197 0.04 0.09 0.7
2001 207 0.04 0.09 0.9
2002 204 0.04 0.09 1.0
2003 194 0.04 0.10 0.8
2004 214 0.04 0.10 0.3
2005 233 0.04 0.10 0.5
2006 251 0.04 0.10 0.7
2007 272 0.04 0.10 2.2
2008 294 0.04 0.10 1.7
2009 311 0.04 0.10 1.6
2010 341 0.04 0.09 2.4
2011 370 0.04 0.10 3.3
2012 391 0.04 0.11 2.7
2013 421 0.04 0.12 3.7
2014 453 0.04 0.13 3.9
2015 487 0.05 0.14 3.7
2016 511 0.05 0.16
Source: World Development Indicators.

Table 4: Determinants of Manufacturing Sector

Year number of permanent manufacturing FDI, net Manufactured Inflation
manufacturing employment value added flows % exports per
sector Gdp of GDP capita
2007/08 31 584 4.6 1.13 2.2 17.2
2008/09 38.8 309 4.1 0.4 1.7 44.4
2009/10 43.00 1193 3.9 0.68 1.6 8.5
2010/11 49.80 1357 4 0.96 2.4 8.1
2011/12 59.6 2642 3.7 1.96 3.3 33.2
2012/13 73.9 7586 3.4 0.64 2.7 24.1
2013/14 89.5 7007 3.7 2.28 3.7 8.1
2014/15 103.7 6016 4 3.34 3.9 7.4
2015/16 125 4588 4.4 4.07 3.7 10.1
2016/17 403.4 5989 5.6 5.51 3.8 7.3

Table 5: Model Summary

Model R R Adjusted Std. Error Change Statistics

Square R Square of the R Square F df1 df2 Sig. F
Estimate Change Change Change
1 .987a .974 .941 8.43483 .974 29.526 5 4 .003
a. Predictors: (Constant), inflation, manufacturing value added, permanent employ,
manufacturing export per capita, FDI net flow

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 Table 6: Coefficients (Dependent Variable: Manufacturing Sector GDP)
Model Unstandardized Standardized t Sig. 95.0% Confidence
Coefficients Coefficients Interval for B
B Std. Beta Lower Upper
Error Bound Bound
(Constant) 132.874 56.672 2.345 .079 -24.473 290.222
permanent
.005 .002 .402 2.965 .041 .000 .009
employ
manufacturig
-21.383 11.025 -.402 -1.940 .124 -51.994 9.227
valuadded
1
FDI net flow 24.609 6.914 1.281 3.560 .024 5.414 43.804
manufacturing
export per -14.218 10.404 -.386 -1.367 .244 -43.104 14.668
capita
Inflation .012 .237 .005 .052 .961 -.646 .670

Table 7: ANOVA

Model Sum of Squares Df Mean Square F Sig.

Regression 10503.414 5 2100.683 29.526 .003b
1 Residual 284.586 4 71.146
Total 10788.000 9

a. Dependent Variable: manufacturing sector

b. Predictors: (Constant), inflation, manufacturing value added, permanent employ,
manufacturing export per capita, FDI net flow

Table 8: Descriptive Statistics

Mean Std. Deviation N

manufacturing sector 62.0000 34.62177 10
permanent employ 3727.1000 2819.06645 10
manufacturing value added 4.1400 .61860 10
FDI net flow 2.0970 1.71195 10
manufacturing export per capita 2.9000 .89194 10
Inflation 16.8400 13.02956 10

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