THE EFFECT OF EXCHANGE RATE FLUCTUATION ON THE NIGERIA MANUFACTURING SECTOR (1986-2010)

CHAPTER ONE: INTRODUCTION

1.1 Background of the Study

The exchange rate is one of the most critical macroeconomic variables in any economy, serving as the price of one currency in terms of another. It influences the competitiveness of a nation’s goods and services in international markets, the cost of imported inputs, the value of foreign earnings, and the overall balance of payments position. For developing countries like Nigeria, which are heavily dependent on imports for capital goods, machinery, raw materials, and intermediate products, the exchange rate assumes even greater significance. Fluctuations in the exchange rate—whether depreciation, appreciation, or volatility—can have profound effects on the real sector of the economy, particularly manufacturing (CBN, 2019; Odularu and Okonkwo, 2009).

Nigeria’s exchange rate policy has undergone dramatic transformations since independence in 1960, but the period from 1986 to 2010 is particularly significant. Prior to 1986, Nigeria operated a fixed exchange rate regime under which the Central Bank of Nigeria (CBN) pegged the Naira to the British Pound and later to a basket of currencies. However, falling oil prices in the early 1980s led to severe balance of payments crises, foreign exchange shortages, and economic recession. In response, the government adopted the Structural Adjustment Programme (SAP) in 1986, which introduced the Second-Tier Foreign Exchange Market (SFEM) and effectively floated the Naira. This marked the beginning of a managed float regime characterized by periodic adjustments, depreciation pressures, and significant exchange rate volatility (Obadan, 2006; Soludo, 2008).

The period 1986–2010 witnessed several distinct exchange rate regimes. From 1986 to 1993, Nigeria operated various versions of a dual exchange rate system and later a managed float. Between 1994 and 1999, a fixed regime was re-introduced following the abandonment of SAP, with the official rate pegged at N21.99 to N22.05 per US dollar. From 1999 to 2010, under civilian administrations, the CBN adopted a managed float regime with periodic devaluations and the introduction of the Wholesale Dutch Auction System (WDAS) in 2006. Throughout this period, the Naira depreciated from about N1.00 per US dollar in the early 1980s to approximately N150 per US dollar by 2010—a cumulative depreciation of over 14,000 percent (CBN Statistical Bulletin, 2011; Uche and Ehikwe, 2010).

The manufacturing sector in Nigeria has historically been seen as the engine of economic diversification and sustainable development. At independence in 1960, manufacturing contributed modestly to GDP, but through protectionist policies in the 1970s, the sector grew to account for about 10-15 percent of GDP by the early 1980s. However, the sector has since struggled, with its contribution declining to single digits by the 1990s and remaining below 10 percent through 2010. This decline coincided with the period of exchange rate liberalization and volatility, raising important questions about the relationship between exchange rate fluctuations and manufacturing performance (Adenikinju, 2005; Ogbu, 2007).

Theoretical literature provides conflicting predictions about the effect of exchange rate fluctuations on manufacturing. On one hand, depreciation (a weakening of the domestic currency) should make domestic manufactured goods cheaper in international markets, boosting exports, and make imports more expensive, encouraging domestic production of import substitutes (the expenditure-switching effect). On the other hand, depreciation increases the cost of imported machinery, spare parts, raw materials, and intermediate inputs—all of which are heavily relied upon by Nigerian manufacturers. Since the manufacturing sector in Nigeria is characterized by low local content and high import dependence, the cost-increasing effect of depreciation may outweigh any export competitiveness gains (Krugman and Obstfeld, 2009; Arize, 2015).

Empirical evidence on the effect of exchange rate fluctuations on manufacturing in Nigeria is mixed and often contradictory. Some studies have found that exchange rate depreciation negatively affects manufacturing output, capacity utilization, and value-added because of high import dependence. Other studies have found that exchange rate volatility (uncertainty about future exchange rate movements) discourages investment in the manufacturing sector, as firms delay capital expenditures and new projects when they cannot predict the future cost of imported inputs. Still other studies have found that a stable and competitive exchange rate is more important for manufacturing growth than the level of the rate itself (Ibrahim, 2007; Nwankwo, 2010).

The period 1986–2010 is particularly instructive because it captures both the initial liberalization under SAP and the subsequent periods of adjustment, crisis, and reform. During this period, Nigeria experienced major external shocks, including the Gulf War (1990-1991), the Asian financial crisis (1997-1998), the global commodity price boom (2000-2008), and the global financial crisis (2008-2009). Each of these shocks transmitted to the Nigerian economy partly through exchange rate movements. Manufacturing firms, particularly those in import-dependent subsectors such as pharmaceuticals, textiles, electronics assembly, and machinery, had to navigate this turbulent environment with varying degrees of success (Ekpo and Umoh, 2004).

Several indicators of manufacturing sector performance can be examined in relation to exchange rate fluctuations. Manufacturing value-added (MVA) as a percentage of GDP declined from about 8-10 percent in the mid-1980s to about 4 percent by the late 1990s, recovering modestly to about 6-7 percent by 2010. Capacity utilization in manufacturing, which averaged over 70 percent in the early 1980s, fell to below 40 percent by the mid-1990s and only recovered to about 55-60 percent by 2010. The number of active manufacturing firms declined, and many firms that survived did so by reducing their workforce, operating below capacity, or shifting to less import-intensive activities. These trends suggest a negative relationship between exchange rate fluctuations and manufacturing performance (UNIDO, 2009; MAN, 2005).

However, the relationship is not simply one of cause and effect. Other factors also influenced manufacturing performance during this period, including inadequate infrastructure (particularly electricity), poor transportation networks, policy inconsistency, high interest rates, security challenges, and competition from cheaper imports (both legal and smuggled). Disentangling the specific effect of exchange rate fluctuations from these other factors is a key methodological challenge. Nevertheless, given the extreme volatility of the Naira during this period—with multiple devaluations and wide gaps between official and parallel market rates—it is plausible that exchange rate fluctuations were a major determinant of manufacturing sector outcomes (Oyejide, 2006; Ogbu, 2007).

The manufacturing sector is of strategic importance to Nigeria’s long-term development. Unlike oil and gas, which are capital-intensive and create relatively few jobs, manufacturing has significant forward and backward linkages with agriculture, services, and other sectors. A strong manufacturing sector can absorb large numbers of workers, reduce import dependence, promote technological learning, and diversify the export base away from oil. Yet, despite decades of policy pronouncements about the need to industrialize, Nigeria remains heavily dependent on imported manufactured goods, from machinery and chemicals to basic consumer goods like textiles, pharmaceuticals, and processed foods. Understanding the role of exchange rate fluctuations in shaping manufacturing performance is therefore not merely an academic exercise but a policy imperative (Adenikinju, 2005; Soludo, 2008).

The choice of the time frame 1986–2010 allows for a comprehensive analysis that covers two and a half decades of post-SAP experience. By 1986, SAP had begun, marking a structural break from the previous fixed exchange rate regime. By 2010, Nigeria had experienced over a decade of civilian democracy, several exchange rate policy reforms, and the aftermath of the global financial crisis. This period provides sufficient data points for time-series analysis, captures multiple business cycles, and includes both periods of relative stability and periods of extreme volatility. More recent data (post-2010) could be examined in future research, but the 1986–2010 window is long enough to draw meaningful statistical conclusions (CBN, 2011; NBS, 2010).

Finally, this study is situated within a broader literature on exchange rate policy and real sector performance in developing economies. Countries such as Ghana, Kenya, South Africa, and Brazil have all grappled with similar challenges of exchange rate management and manufacturing development. Comparative insights from these countries suggest that exchange rate stability, coupled with industrial policy measures such as local content requirements, export incentives, and infrastructure investment, can mitigate the negative effects of fluctuations on manufacturing. Nigeria’s experience from 1986 to 2010 offers lessons for policymakers seeking to revive the manufacturing sector as a driver of economic diversification and job creation (Rodrik, 2008; Arize, 2015).

1.2 Statement of the Problem

Despite decades of policy reforms, including trade liberalization, exchange rate deregulation, and various industrial development initiatives, the Nigerian manufacturing sector has experienced persistent decline or stagnation from 1986 to 2010. Key indicators such as manufacturing value-added as a percentage of GDP, capacity utilization, employment share, and contribution to non-oil exports all trended downward during much of this period. Concurrently, the Naira exchange rate experienced extreme fluctuations, including multiple devaluations, wide parallel market premiums, and periods of high volatility. While theoretical reasoning suggests that exchange rate fluctuations should affect manufacturing through import cost channels, export competitiveness, and investment uncertainty, the specific nature, magnitude, and direction of this effect in the Nigerian context remain inadequately understood. Existing empirical studies have produced conflicting findings, often due to differences in methodology, time period, or data sources. Furthermore, many studies have focused on short-term effects or have aggregated manufacturing without considering subsectoral differences in import dependence and export orientation. The critical problem, therefore, is the lack of a rigorous, comprehensive, and time-series-based analysis of how exchange rate fluctuations affected the Nigerian manufacturing sector over the sustained period of 1986–2010. This study is motivated to fill this gap by empirically investigating the effect of exchange rate fluctuations (both level changes and volatility) on key manufacturing performance indicators.

1.3 Aim of the Study

The aim of this study is to examine the effect of exchange rate fluctuations on the performance of the Nigerian manufacturing sector over the period 1986 to 2010.

1.4 Objectives of the Study

The specific objectives of this study are to:

1. Examine the trend of exchange rate fluctuations and manufacturing sector performance in Nigeria from 1986 to 2010.
2. Determine the effect of exchange rate depreciation on manufacturing output (value-added) in Nigeria during the study period.
3. Assess the impact of exchange rate volatility on capacity utilization in the Nigerian manufacturing sector.
4. Analyze the effect of exchange rate fluctuations on manufacturing export performance.
5. Evaluate the relationship between exchange rate fluctuations and the import content of manufactured goods in Nigeria.

1.5 Research Questions

The following research questions guide this study:

1. What were the trends of exchange rate fluctuations and manufacturing sector performance in Nigeria from 1986 to 2010?
2. What is the effect of exchange rate depreciation on manufacturing output (value-added) in Nigeria?
3. How does exchange rate volatility affect capacity utilization in the Nigerian manufacturing sector?
4. What impact do exchange rate fluctuations have on the export performance of Nigerian manufactured goods?
5. What is the relationship between exchange rate fluctuations and the import content of manufactured goods in Nigeria?

1.6 Research Hypotheses

The following hypotheses are formulated in null (H₀) and alternative (H₁) forms:

Hypothesis One

• H₀: Exchange rate depreciation has no significant effect on manufacturing output (value-added) in Nigeria from 1986 to 2010.
• H₁: Exchange rate depreciation has a significant effect on manufacturing output (value-added) in Nigeria from 1986 to 2010.

Hypothesis Two

• H₀: Exchange rate volatility has no significant impact on capacity utilization in the Nigerian manufacturing sector.
• H₁: Exchange rate volatility has a significant impact on capacity utilization in the Nigerian manufacturing sector.

Hypothesis Three

• H₀: There is no significant relationship between exchange rate fluctuations and manufacturing export performance in Nigeria.
• H₁: There is a significant relationship between exchange rate fluctuations and manufacturing export performance in Nigeria.

Hypothesis Four

• H₀: Exchange rate fluctuations do not significantly affect the import content of manufactured goods in Nigeria.
• H₁: Exchange rate fluctuations significantly affect the import content of manufactured goods in Nigeria.

1.7 Significance of the Study

This study is significant for several stakeholders. First, policymakers at the Central Bank of Nigeria, the Federal Ministry of Industry, Trade and Investment, and the National Planning Commission will benefit from empirical evidence on how exchange rate fluctuations affect manufacturing, enabling them to design more coherent and effective exchange rate policies that support industrial development. Second, manufacturing firms and their associations (such as the Manufacturers Association of Nigeria, MAN) can use the findings to advocate for policy reforms and to develop hedging strategies to manage exchange rate risk. Third, academics and researchers will find value in the study’s contribution to the literature on exchange rate economics and industrial development in Nigeria, particularly the under-researched period of 1986–2010. Fourth, international development partners and donors interested in supporting Nigerian industrialization will gain insights into the macroeconomic constraints facing the manufacturing sector. Fifth, students of economics, finance, and development studies will find the study useful as a reference for understanding the relationship between exchange rate policy and real sector performance. Finally, the broader Nigerian economy will benefit if improved understanding of exchange rate-manufacturing linkages leads to policies that revive the manufacturing sector, create jobs, reduce import dependence, and diversify the economy away from oil.

1.8 Scope of the Study

This study focuses on the effect of exchange rate fluctuations on the Nigerian manufacturing sector over the period 1986 to 2010. The time frame is specifically chosen to begin with the introduction of the Structural Adjustment Programme (SAP) and the associated liberalization of the exchange rate regime in 1986, and to end in 2010, providing a 25-year period for analysis. Geographically, the study covers the entire Nigerian manufacturing sector at the national level, using aggregated time-series data. In terms of variables, the study examines exchange rate fluctuations measured by both the nominal exchange rate (Naira per US dollar) and real effective exchange rate (REER), as well as exchange rate volatility (measured using standard deviation or GARCH-based methods). Manufacturing performance is measured by manufacturing value-added (MVA) as a percentage of GDP, capacity utilization rates, manufacturing exports as a percentage of total exports, and the import content of manufactured goods. Data sources include the Central Bank of Nigeria Statistical Bulletin, National Bureau of Statistics publications, Manufacturers Association of Nigeria reports, World Bank Development Indicators, and UNIDO databases. The study does not extend beyond 2010, nor does it cover other sectors such as agriculture or services.

1.9 Definition of Terms

Exchange Rate: The price of one currency in terms of another. In this study, it refers to the official Naira-to-US dollar exchange rate as published by the Central Bank of Nigeria.

Exchange Rate Fluctuation: Changes in the exchange rate over time, including both depreciation (fall in the value of the Naira) and appreciation (rise in the value of the Naira), as well as volatility (the degree of variability or uncertainty around the exchange rate).

Exchange Rate Depreciation: A decrease in the value of the Naira relative to foreign currencies, meaning that more Naira are required to purchase one unit of foreign currency (e.g., US dollar).

Exchange Rate Volatility: The degree of variation or instability in the exchange rate over a given period, often measured by the standard deviation of exchange rate changes or by conditional variance models such as GARCH.

Manufacturing Sector: The segment of the economy engaged in the physical or chemical transformation of materials, substances, or components into new products. This includes food processing, textiles, chemicals, pharmaceuticals, cement, metal fabrication, machinery, electronics assembly, and other industrial activities.

Manufacturing Value-Added (MVA): The net output of the manufacturing sector after subtracting intermediate inputs from gross output. It is often expressed as a percentage of Gross Domestic Product (GDP).

Capacity Utilization: The ratio of actual output produced by manufacturing firms to the maximum possible output that could be produced with existing plant, equipment, and labor, usually expressed as a percentage.

Import Content: The proportion of imported raw materials, intermediate goods, and capital goods used in the production of manufactured goods. High import content indicates dependence on foreign inputs.

Structural Adjustment Programme (SAP): A set of economic policies introduced in Nigeria in 1986, including trade liberalization, exchange rate deregulation, privatization, and fiscal austerity, aimed at addressing balance of payments problems and promoting market-oriented growth.

Real Effective Exchange Rate (REER): The nominal exchange rate adjusted for relative price levels (inflation) between Nigeria and its trading partners, providing a measure of international competitiveness.

CHAPTER TWO: LITERATURE REVIEW

2.1 Conceptual Framework

A conceptual framework is a structural representation of the key concepts or variables in a study and the hypothesized relationships among them. It serves as the analytical lens through which the researcher organizes the study, selects appropriate methodology, and interprets findings. In this study, the conceptual framework is built around two primary constructs: Exchange Rate Fluctuation (the independent variable) and Manufacturing Sector Performance (the dependent variable). Additionally, certain intervening and moderating variables are recognized as influencing the strength and direction of the relationship (Miles, Huberman, and Saldaña, 2020).

The independent variable, Exchange Rate Fluctuation, refers to the changes in the value of the Naira relative to foreign currencies, particularly the US dollar, over time. For the purpose of this study, exchange rate fluctuation is conceptualized along three measurable dimensions: (a) exchange rate level (the actual Naira per US dollar rate, capturing depreciation or appreciation), (b) exchange rate volatility (the degree of variability or uncertainty around the exchange rate, often measured by standard deviation or GARCH-based conditional variance), and (c) exchange rate misalignment (the deviation of the actual exchange rate from its equilibrium level). Each dimension captures a different aspect of how exchange rate movements may affect manufacturing firms (CBN, 2011; Obadan, 2006).

The dependent variable, Manufacturing Sector Performance, is a multidimensional construct that reflects how well the manufacturing sector achieves its economic objectives. In this study, manufacturing sector performance is conceptualized along four key indicators relevant to the Nigerian context over the period 1986–2010: (a) manufacturing output (measured by manufacturing value-added as a percentage of GDP and real manufacturing output indices), (b) capacity utilization (the ratio of actual output to potential output, expressed as a percentage), (c) manufacturing export performance (manufactured exports as a percentage of total exports or as a percentage of manufacturing output), and (d) import intensity (the ratio of imported inputs to total manufacturing inputs, indicating dependence on foreign raw materials and components). These indicators collectively capture both the scale and efficiency of manufacturing activity (Adenikinju, 2005; Ogbu, 2007).

The conceptual framework posits a relationship between exchange rate fluctuations and manufacturing sector performance, but the direction of this relationship is theoretically ambiguous and depends on several factors. On one hand, exchange rate depreciation (a weaker Naira) should, in theory, make Nigerian manufactured goods cheaper in international markets, boosting exports (the expenditure-switching effect). Depreciation also makes imports more expensive, encouraging domestic production of import substitutes. On the other hand, depreciation increases the cost of imported machinery, spare parts, raw materials, and intermediate inputs—all of which are heavily relied upon by Nigerian manufacturers. Since the manufacturing sector in Nigeria is characterized by low local content and high import dependence, the cost-increasing effect of depreciation may outweigh any export competitiveness gains (Krugman and Obstfeld, 2009; Arize, 2015).

The framework also distinguishes between the effects of exchange rate level changes (depreciation or appreciation) and the effects of exchange rate volatility (uncertainty). Even if the level of the exchange rate is favorable (e.g., a competitive depreciation), high volatility creates uncertainty that discourages investment. Manufacturing firms, when faced with unpredictable future exchange rates, may delay or cancel investments in new plant, equipment, or product lines because they cannot reliably forecast the cost of imported inputs or the revenue from exports. This investment uncertainty channel is distinct from the level effect and may be equally or more important in explaining manufacturing sector decline in Nigeria during periods of extreme exchange rate instability (Ibrahim, 2007; Nwankwo, 2010).

An important feature of this conceptual framework is the recognition of intervening and moderating variables that may influence the relationship between exchange rate fluctuations and manufacturing performance. These include: (a) trade openness (the degree to which the manufacturing sector is exposed to international competition), (b) import dependence (the proportion of inputs sourced from abroad), (c) export orientation (the share of output sold in international markets), (d) access to foreign exchange (the ability of manufacturers to obtain foreign currency at official rates), (e) infrastructure quality (particularly electricity supply and transportation networks, which affect production costs), (f) monetary policy (interest rates and credit availability), and (g) fiscal policy (taxes, subsidies, and tariff protection). In the Nigerian context, the high import dependence of manufacturing is particularly important; firms that rely heavily on imported raw materials are more vulnerable to exchange rate depreciation than firms that source locally (Oyejide, 2006; Ekpo and Umoh, 2004).

The conceptual framework also acknowledges potential lagged and non-linear effects. Exchange rate fluctuations may not affect manufacturing performance immediately; there may be a lag as firms adjust their production plans, draw down existing inventories of imported inputs, or renegotiate contracts. Additionally, the effect may be non-linear: small depreciations may have minimal effects, but large depreciations (such as the sharp devaluations experienced in Nigeria in the late 1980s and early 1990s) may trigger severe disruptions. Similarly, the effect of depreciation may be asymmetric: a depreciation may hurt manufacturing more than an appreciation helps, because input costs adjust upward quickly while export competitiveness gains take time to materialize. The framework incorporates these complexities by specifying that the relationship between exchange rate fluctuations and manufacturing performance should be modeled with appropriate lags and non-linear specifications (Ibrahim, 2007).

Methodologically, the conceptual framework guides the selection of econometric techniques and variables. Time-series data on exchange rates (official and parallel market rates), manufacturing output, capacity utilization, exports, and imports are collected for the period 1986–2010. Exchange rate volatility is computed using methods such as the standard deviation of exchange rate changes or a GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model. The relationship is estimated using techniques such as Ordinary Least Squares (OLS), cointegration analysis (to test for long-run relationships), and Error Correction Models (ECM) to distinguish short-run from long-run effects. Control variables (such as GDP growth, inflation, interest rates, and trade openness) are included to avoid omitted variable bias (Gujarati and Porter, 2009).

Empirical studies that have employed similar conceptual frameworks in other developing countries provide validation for this approach. For example, studies on Ghana’s manufacturing sector found that exchange rate depreciation had a net negative effect on manufacturing output due to high import dependence, while studies on South Africa found a positive effect for more export-oriented subsectors. In Kenya, exchange rate volatility was found to be more damaging than the level of depreciation, as it discouraged long-term investment in manufacturing capacity. These cross-country differences underscore the importance of country-specific analysis and highlight the need for the current study on Nigeria (Arize, 2015; Rodrik, 2008).

The conceptual framework also addresses the historical specificity of the 1986–2010 period. This period witnessed the introduction of the Structural Adjustment Programme (SAP) in 1986, which liberalized the exchange rate regime, the re-fixing of the rate in 1994, the return to managed floating in 1999, and the introduction of the Wholesale Dutch Auction System (WDAS) in 2006. Each regime change created different patterns of exchange rate behavior and manufacturing responses. The framework acknowledges that the relationship between exchange rate fluctuations and manufacturing performance may not be stable over the entire period and that structural breaks (changes in policy regime) should be tested for and accounted for in the analysis (Obadan, 2006; Soludo, 2008).

Visually, the conceptual framework for this study can be represented as a diagram with Exchange Rate Fluctuation (independent variable) shown with an arrow pointing to Manufacturing Sector Performance (dependent variable). Exchange rate fluctuation is broken into three boxes (level, volatility, misalignment). Manufacturing performance is broken into four boxes (output, capacity utilization, exports, import intensity). Along the connecting arrow are placed the moderating variables (import dependence, export orientation, infrastructure, trade openness). Below the arrow, lagged and non-linear effects are indicated. This visual representation aids readers in quickly grasping the hypothesized relationships and is consistent with standard practice in macroeconomic and trade research (Saunders, Lewis, and Thornhill, 2019).

In summary, the conceptual framework of this study provides a clear, logical, and empirically grounded structure for investigating how exchange rate fluctuations affected the Nigerian manufacturing sector from 1986 to 2010. By disaggregating both exchange rate fluctuation and manufacturing performance into measurable dimensions and acknowledging the role of intervening factors, lags, and non-linearities, the framework enhances the validity and reliability of the research findings. It also serves as a bridge between the theoretical foundations (discussed in section 2.2) and the empirical investigation (chapters three and four) (Creswell and Creswell, 2018).

2.2 Theoretical Framework

A theoretical framework is a collection of interrelated concepts, definitions, and propositions that present a systematic view of phenomena by specifying relationships among variables, with the purpose of explaining and predicting those phenomena. In this study, four major theories are adopted to explain the relationship between exchange rate fluctuations and manufacturing sector performance: the Purchasing Power Parity (PPP) Theory, the Elasticity Approach (Marshall-Lerner Condition), the J-Curve Theory, and the Exchange Rate Pass-Through Theory. These theories collectively provide a robust lens for understanding how and why exchange rate fluctuations affect manufacturing output, capacity utilization, exports, and import dependence in the Nigerian context (Cassel, 1918; Marshall, 1923; Lerner, 1944; Magee, 1973).

2.2.1 Purchasing Power Parity (PPP) Theory

The Purchasing Power Parity (PPP) Theory, originally developed by Swedish economist Gustav Cassel in 1918, is one of the oldest and most fundamental theories of exchange rate determination. The theory posits that in the long run, exchange rates should adjust so that the same basket of goods costs the same in different countries when measured in a common currency. The absolute version of PPP states that the exchange rate between two currencies equals the ratio of the price levels in the two countries. The relative version states that the percentage change in the exchange rate equals the difference between the inflation rates of the two countries. While PPP is often violated in the short run due to transaction costs, trade barriers, and non-traded goods, it provides a long-run anchor for exchange rate expectations (Cassel, 1918; Rogoff, 1996).

In the context of this study, PPP Theory explains why persistent inflation differentials between Nigeria and its trading partners led to sustained depreciation of the Naira during the 1986–2010 period. Nigeria experienced high inflation, often in double digits, while major trading partners (particularly the US, UK, and EU) had relatively lower inflation. According to PPP, the Naira should depreciate approximately by the inflation differential. This depreciation, while predictable in the long run, creates challenges for manufacturing firms that must plan investment, pricing, and sourcing decisions over shorter time horizons. If Nigerian manufacturers expect further depreciation based on persistent inflation differentials, they may raise prices preemptively, reducing competitiveness, or they may shift to imported inputs (which become more expensive) without corresponding increases in local sourcing (Obadan, 2006; Odularu and Okonkwo, 2009).

PPP Theory also implies that deviations from PPP (real exchange rate misalignment) affect the competitiveness of the manufacturing sector. When the Naira is overvalued relative to PPP (i.e., the real exchange rate is too strong), Nigerian manufactured goods become expensive relative to foreign competitors, hurting exports and encouraging imports. When the Naira is undervalued (weak real exchange rate), manufactured goods become more competitive internationally, potentially boosting exports and import substitution. During the 1986–2010 period, Nigeria experienced episodes of both overvaluation (e.g., the fixed regime of 1994–1999) and undervaluation (e.g., after the initial SAP devaluation). The theory suggests that manufacturing performance should be better during periods of undervaluation, provided that other conditions (such as access to imported inputs) are met (Rodrik, 2008; Oyejide, 2006).

Empirical tests of PPP in Nigeria have generally found that PPP holds weakly or only in the very long run, with large and persistent deviations in the short to medium term. This means that real exchange rate misalignments can persist for years, creating extended periods of either competitive advantage or disadvantage for manufacturing firms. For policymakers, PPP Theory provides a benchmark for assessing whether the exchange rate is broadly appropriate for industrial development. For manufacturing firms, PPP informs expectations about future exchange rate movements based on inflation differentials, helping them manage risk (Adenikinju, 2005; Ekpo and Umoh, 2004).

2.2.2 Elasticity Approach (Marshall-Lerner Condition)

The Elasticity Approach, associated with economists Alfred Marshall, Abba Lerner, and Joan Robinson, focuses on how exchange rate changes affect a country’s trade balance through changes in the relative prices of exports and imports. The Marshall-Lerner Condition states that a depreciation (devaluation) will improve a country’s trade balance if and only if the sum of the price elasticities of demand for exports and imports (in absolute value) is greater than one. Intuitively, if demand for exports is price-elastic (foreign buyers respond strongly to lower prices caused by depreciation), export volumes will increase sufficiently to offset the lower foreign currency price. Similarly, if demand for imports is price-elastic (domestic buyers reduce imports significantly when import prices rise due to depreciation), import volumes will fall enough to offset the higher cost of remaining imports (Marshall, 1923; Lerner, 1944).

In the context of this study, the Elasticity Approach explains whether exchange rate depreciation can be expected to improve the trade balance and, by extension, benefit the manufacturing sector. For depreciation to benefit Nigerian manufacturing, the Marshall-Lerner Condition must hold: the sum of the export demand elasticity and the import demand elasticity (in absolute terms) must exceed one. However, empirical evidence suggests that in many developing countries, including Nigeria, demand for both exports and imports is relatively price-inelastic in the short to medium run. Nigerian manufactured exports face low demand elasticities because they are often primary commodities or low-value-added goods with few substitutes. Import demand may also be inelastic because many manufactured goods (machinery, chemicals, pharmaceuticals) have few domestic substitutes, so manufacturers continue to import even when prices rise (Krugman and Obstfeld, 2009; Ogbu, 2007).

The Elasticity Approach also highlights the importance of supply-side responses. Even if the Marshall-Lerner Condition holds, the beneficial effects of depreciation on manufacturing exports and import substitution will not materialize if domestic manufacturers cannot increase output in response to improved incentives. Capacity constraints, lack of working capital, poor infrastructure, and shortages of imported inputs (which become more expensive after depreciation) can prevent the supply response needed to realize the benefits of a weaker currency. In Nigeria, chronic low capacity utilization (often below 50% during the 1990s) suggests that supply-side constraints significantly limited the ability of manufacturers to respond to exchange rate incentives (Ibrahim, 2007; Nwankwo, 2010).

Empirical applications of the Elasticity Approach to Nigeria have yielded mixed results. Some studies have found that the Marshall-Lerner Condition is satisfied in the long run but not in the short run, implying that depreciation eventually improves the trade balance but only after a period of deterioration (the J-Curve, discussed next). Other studies have found that the condition is not satisfied at all, meaning that depreciation actually worsens Nigeria’s trade balance because import demand is highly inelastic while export demand is also inelastic. For manufacturing, this suggests that depreciation may hurt more than it helps, as the cost of imported inputs rises sharply without a corresponding increase in export volumes or domestic sales (Obadan, 2006; Odularu and Okonkwo, 2009).

2.2.3 J-Curve Theory

The J-Curve Theory, developed by Stephen Magee (1973) and others, extends the Elasticity Approach by focusing on the time path of the trade balance following an exchange rate depreciation. The theory posits that following a depreciation, the trade balance initially worsens (becomes more negative or less positive) before eventually improving, tracing a pattern that resembles the letter “J”. The initial deterioration occurs because, in the short run, the volumes of exports and imports adjust slowly (due to existing contracts, habits, and adjustment costs), while the prices adjust immediately. Since the price of imports rises immediately but import volumes do not fall as quickly, the import bill in domestic currency increases. Similarly, export volumes do not rise immediately, so export revenues in domestic currency may initially fall. Only after sufficient time has passed for volumes to adjust does the trade balance improve (Magee, 1973; Bahmani-Oskooee and Ratha, 2004).

In the context of this study, the J-Curve Theory explains why the negative effects of exchange rate depreciation on Nigerian manufacturing may be observed first, with positive effects (if any) only appearing after a lag. When the Naira depreciates, manufacturers immediately face higher costs for imported raw materials, spare parts, and machinery. However, they cannot immediately pass these costs on to customers (especially in competitive markets) or switch to local suppliers (if local alternatives do not exist). Profits are squeezed, and some firms may reduce output or close. On the export side, Nigerian manufactured goods become cheaper in foreign currency, but it takes time for foreign buyers to discover new suppliers, adjust their purchasing habits, and for Nigerian firms to increase export capacity. Thus, the short-run effect of depreciation is likely to be negative for manufacturing, with any positive effects only emerging in the medium to long term (Oyejide, 2006; Arize, 2015).

The J-Curve Theory also has implications for policy duration and credibility. If policymakers expect depreciation to quickly improve manufacturing performance, they may be disappointed by short-run negative outcomes and reverse course before the positive long-run effects materialize. For Nigerian manufacturing, which faced repeated devaluations followed by periods of fixed or overvalued exchange rates, the J-Curve suggests that the positive effects of depreciation may never have had time to fully materialize before policy shifted. This underscores the importance of exchange rate stability and policy consistency for manufacturing development (Soludo, 2008; Ekpo and Umoh, 2004).

Empirical studies of the J-Curve in Nigeria have generally found evidence of an initial deterioration followed by a gradual improvement in the trade balance, though the magnitude and duration of the J-curve effect vary across studies. For manufacturing specifically, the evidence is less clear, with some studies finding that depreciation has persistent negative effects on manufacturing output due to the high import content of production. The J-Curve Theory thus provides a useful framework for understanding the dynamic, time-varying effects of exchange rate fluctuations on manufacturing, which is essential for correctly specifying econometric models with appropriate lags (Ibrahim, 2007; Nwankwo, 2010).

2.2.4 Exchange Rate Pass-Through Theory

Exchange Rate Pass-Through (ERPT) Theory examines the extent to which changes in the exchange rate are reflected in domestic prices of imported and exported goods. Complete pass-through means that a 1% depreciation leads to a 1% increase in the domestic currency price of imports. Incomplete pass-through means that import prices rise by less than the depreciation, implying that foreign exporters absorb some of the exchange rate change in their profit margins. ERPT is influenced by factors such as the market structure (degree of competition), the share of imported inputs in production, the presence of pricing-to-market behavior, and the monetary policy regime (Goldberg and Knetter, 1997; Campa and Goldberg, 2005).

In the context of this study, ERPT Theory explains how exchange rate fluctuations transmit to manufacturing costs and prices. If pass-through is high, a depreciation leads to a sharp increase in the Naira cost of imported raw materials, machinery, and intermediate goods, directly raising production costs for manufacturers. If pass-through is low, the impact on costs is muted, giving manufacturers more time to adjust. However, low pass-through may also indicate that foreign suppliers have market power and can adjust prices strategically, which may not be beneficial to Nigerian manufacturers in the long run. Understanding the degree of ERPT is essential for predicting how exchange rate fluctuations affect manufacturing costs, profit margins, and ultimately output and capacity utilization (Adenikinju, 2005; Ogbu, 2007).

ERPT Theory also has implications for inflation and monetary policy, which indirectly affect manufacturing. If exchange rate depreciation leads to high pass-through to consumer prices (via imported consumer goods and imported inputs for locally produced consumer goods), the central bank may respond by raising interest rates to contain inflation. Higher interest rates increase the cost of working capital for manufacturers, further depressing output and investment. Thus, the manufacturing sector can be affected by exchange rate fluctuations both directly (through input costs) and indirectly (through monetary policy responses). In Nigeria, periods of sharp depreciation have often been followed by tighter monetary policy, compounding the challenges facing manufacturers (Obadan, 2006; CBN, 2011).

Empirical studies of ERPT in Nigeria have found that pass-through is relatively high, especially for manufactured goods and machinery. This means that depreciation quickly translates into higher production costs for manufacturers. Moreover, pass-through is asymmetric: depreciation leads to faster and larger price increases than appreciation leads to price decreases. This asymmetry means that manufacturing firms face a “ratchet effect”—costs rise quickly when the Naira falls but do not fall as quickly when the Naira strengthens. Over the 1986–2010 period, with the Naira experiencing a sustained downward trend, this asymmetry implies a persistent upward pressure on manufacturing costs, contributing to the sector’s overall decline (Odularu and Okonkwo, 2009; Nwankwo, 2010).

2.2.5 Synthesis of the Four Theories

Taken together, PPP Theory, the Elasticity Approach (Marshall-Lerner Condition), J-Curve Theory, and Exchange Rate Pass-Through Theory provide a multi-layered theoretical foundation for this study. PPP Theory explains the long-run relationship between exchange rates and price levels, providing a benchmark for identifying misalignment and understanding the fundamental drivers of Naira depreciation. The Elasticity Approach explains the conditions under which depreciation can improve the trade balance and benefit manufacturing, highlighting the importance of demand elasticities. J-Curve Theory explains the dynamic, time-varying effects of depreciation, showing that negative effects may dominate in the short run while positive effects (if any) emerge only in the longer run. ERPT Theory explains how exchange rate changes transmit to manufacturing costs and prices, and the role of market structure and monetary policy in this transmission (Cassel, 1918; Marshall, 1923; Lerner, 1944; Magee, 1973; Goldberg and Knetter, 1997).

The synthesis of these theories also guides empirical testing. Research questions and hypotheses derived from this theoretical framework can focus on: from PPP Theory, the extent to which real exchange rate misalignment affected manufacturing output; from the Elasticity Approach, whether the Marshall-Lerner Condition holds for Nigerian manufactured goods; from J-Curve Theory, whether the short-run effects of depreciation on manufacturing differ from long-run effects; and from ERPT Theory, the degree to which exchange rate changes are passed through to manufacturing input and output prices. This comprehensive theoretical grounding enhances the validity and richness of the study’s findings (Creswell and Creswell, 2018).

Critically, these theories also acknowledge the importance of structural factors that are specific to Nigeria. The high import dependence of Nigerian manufacturing, low price elasticities of demand for manufactured goods, weak supply-side responses due to infrastructure deficits, and incomplete pass-through due to market concentration all mediate the theoretical predictions. Therefore, the theoretical framework does not assume that depreciation will automatically benefit manufacturing; rather, it specifies the conditions (e.g., high demand elasticities, low import dependence, strong supply response) under which benefits may occur, and it hypothesizes that these conditions were generally not met in Nigeria during 1986–2010 (Oyejide, 2006; Soludo, 2008).

In conclusion, the theoretical framework of this study is firmly anchored in four well-established, complementary theories: Purchasing Power Parity (Cassel, 1918), the Elasticity Approach/Marshall-Lerner Condition (Marshall, 1923; Lerner, 1944), J-Curve Theory (Magee, 1973), and Exchange Rate Pass-Through Theory (Goldberg and Knetter, 1997). These theories collectively explain the mechanisms through which exchange rate fluctuations affect manufacturing sector performance, the conditions under which depreciation may be beneficial or harmful, the dynamic time paths of these effects, and the transmission channels from exchange rates to manufacturing costs and prices. The framework provides a solid foundation for the conceptual framework (section 2.1), the research methodology (chapter three), and the interpretation of findings (chapters four and five) (Saunders et al., 2019).