Does fiscal policy influence industrialization in Sub-Saharan Africa? An explanation using the staggered lag autoregressive (ARDL) panel approach

Technical Summary: Fiscal Policy and Industrialization in Sub-Saharan Africa

Problem Statement
The paper addresses the structural transformation challenges facing Sub-Saharan Africa (SSA), specifically the stagnation and decline of Manufacturing Value Added (MVA) as a share of GDP. While industrialization is recognized as a prerequisite for sustainable economic growth and socio-economic development, SSA countries have largely "sidetracked" the secondary sector, with over 80% of MVA linked to natural resources or low-tech activities. Despite the theoretical consensus that fiscal policy acts as a catalyst for industrialization, empirical evidence regarding its specific impact in SSA remains mixed and under-researched. The study seeks to resolve the debate on whether fiscal policy (proxied by public expenditure) positively or negatively influences industrialization in the region, noting that previous literature has often focused on monetary policy or general economic growth rather than the specific fiscal-industrialization nexus.

Methodology
The study employs a panel Autoregressive Distributed Lag (ARDL) approach, utilizing data from 24 Sub-Saharan African countries over the period 1994–2018. The data is sourced from the World Bank Development Indicators (WDI, 2021).

• Model Specification: The authors adapt the panel ARDL model proposed by Alsaleh and Abdul-Rahim (2019). The dependent variable is Industrialization (INDU), measured by the share of manufacturing value added in GDP. The primary independent variable is Fiscal Policy, proxied by Total Public Expenditure (G). Control variables include Agriculture (AGRI), Services (SERV), and Financial Openness (FDI, measured as Net FDI as a percentage of GDP).
• Estimation Technique: The ARDL approach (Pesaran et al., 2001) is selected for its ability to handle variables with mixed orders of integration (I(0) and I(1)) and its superior performance with small sample sizes compared to conventional cointegration methods like VECM.
• Diagnostic Procedures:
  • Unit Root Testing: The Im, Pesaran, and Shin (IPS) test is used to determine stationarity. Results indicate that Industrialization is integrated of order one [I(1)], while Public Expenditure, Agriculture, Services, and FDI are stationary at levels [I(0)].
  • Lag Selection: The optimal lag structure for the model is determined using the Akaike Information Criterion (AIC), resulting in a (2, 1, 1, 1, 1) specification.
  • Decomposition: The model distinguishes between short-run dynamics and long-run equilibrium relationships.

Key Results
The econometric analysis yields two primary findings regarding the determinants of industrialization in SSA:

1. Positive Influence of Fiscal Policy: Fiscal policy, represented by public expenditure, exerts a positive influence on industrialization. This suggests that government spending acts as a driver for the manufacturing sector's growth in the region.
2. Role of Financial Openness: Financial openness (FDI) also demonstrates a positive coefficient. The study notes that this variable has a more pronounced positive effect in the short run compared to the long run.
3. Negative Impact of Other Sectors: Contrary to some expectations, the study finds that the services and agriculture sectors have a deteriorating effect on manufacturing value added. This implies a potential crowding-out effect or a structural imbalance where resources in these sectors may not be conducive to manufacturing expansion in the current SSA context.

Significance and Claims
The paper positions itself as a timely contribution to economic policy formulation in Sub-Saharan Africa. Its significance is framed around three main points:

• Theoretical Contribution: It addresses a gap in the literature where few studies have specifically isolated public spending as a determinant of industrialization in SSA, moving beyond general growth determinants to focus on the fiscal-industrialization link.
• Methodological Rigor: By utilizing the ARDL panel approach, the study offers a robust estimation technique suitable for the region's data constraints (small samples and mixed integration orders), providing more reliable long-run and short-run dynamics than previous studies.
• Policy Implications: The authors argue that the results provide actionable management elements for authorities. Specifically, they suggest that to reverse deindustrialization, SSA governments must focus on obtaining a return on investment in public sector infrastructure. The paper highlights that the largest shares of national budgets are currently allocated to education and health; therefore, optimizing investment in these areas and public infrastructure is critical for stimulating industrialization.

The study concludes that while fiscal policy is a positive lever for industrialization, the current structural dynamics of the services and agriculture sectors require re-evaluation to ensure they support rather than hinder manufacturing growth.