Economic Uncertainty Steers Zimbabwe’s Remittances Away from Formal Channels

Zimbabwe sits among the world’s most remittance-dependent economies, and a new open-access study argues that the country’s chronic economic uncertainty is actively reshaping how, and how much, money arrives from abroad. Using annual data from 2000 to 2019, economists Talent Kondo, Simba Mutsvangwa and Emiriya Manzote applied an autoregressive distributed lag (ARDL) bounds model and a GARCH volatility model to examine whether uncertainty in the home country deters formal remittance inflows. Their answer is a qualified yes: uncertainty carries a statistically significant negative effect on remittances in both the short run and the long run, even as inflation pushes migrants to send more money to protect their families’ purchasing power.

The study, published in the Springer journal Discover Analytics, measures uncertainty with an index the authors constructed by text-mining Economist Intelligence Unit country reports dedicated specifically to Zimbabwe. Word frequencies tied to domestic shocks, currency transitions, policy inconsistencies and election-related volatility were normalized by total report word count and rescaled to a base of 1,000. The authors describe this as a consistent, objective time-series metric reflecting the information environment that formal remitters and international analysts use to gauge risk. Remittances, measured in annual US dollars, and inflation, measured through the consumer price index because developing economies lack a wholesale price indicator, both came from World Bank data, as did gross domestic product.

The estimation strategy reflects the statistical character of the underlying series. Augmented Dickey-Fuller tests showed the variables to be a mix of stationary at levels and first differences, with none integrated of order two, satisfying the key requirement for the Pesaran bounds cointegration approach. The bounds test F-statistic exceeded the upper critical value, confirming a long-run relationship among remittances, uncertainty, inflation and GDP. Further diagnostics supported the model: Breusch-Godfrey serial correlation tests found no autocorrelation, heteroscedasticity tests indicated homoscedastic residuals, a Ramsey RESET test suggested correct specification, and CUSUM and CUSUM of squares plots stayed within their confidence bands, indicating parameter stability over the sample period.

The headline coefficients are striking. Uncertainty shows a negative effect of −8.77 in the short run and −2.93 in the long run, with the long-run estimate significant at the 5 percent level (p = 0.0328). The authors interpret this as evidence that extreme policy uncertainty generates distrust, prompting remitters to hold back transfers or divert money toward informal channels to avoid value erosion. Zimbabwe’s repeated currency reforms, from the multi-currency era to the Zimbabwe Dollar and later the gold-backed ZiG introduced in early 2024, have cultivated what the authors call a profound trust deficit, forcing diaspora senders to act as rational risk-averters who prioritize capital safety over immediate intervention during high-risk periods.

Equally notable is the speed at which the system returns to equilibrium. The error correction term implies an adjustment rate of 85.1 percent per period (p = 0.0011), meaning that roughly four-fifths of any short-run deviation from the long-run relationship is corrected within a single year. The authors read this rapid reversion as a sign that the diaspora-home country link is highly responsive to equilibrium conditions, even while the level of formal flows is suppressed by uncertainty. Inflation, by contrast, behaves as an altruistic pull factor: it positively influences remittances in both the long run (p = 0.0214) and the short run (p = 0.0362), consistent with migrants raising transfers as living costs rise so that households can maintain their purchasing power.

Gross domestic product adds a third dimension. The long-run GDP coefficient is positive and highly significant at 0.8128 (p = 0.0024), which the authors attribute to an investment-driven motive: as the home economy grows, the diaspora perceives a maturing environment with lower risk and shifts from necessity-based transfers toward strategic capital accumulation in assets such as real estate, facilitated by diaspora-specific instruments from banks including CBZ and CABS. Short-term GDP fluctuations, however, have a negligible effect on remittances, suggesting that remitter confidence responds to sustained growth rather than year-to-year blips.

The volatility analysis tells a more nuanced story. In the GARCH (1,1) framework, the high ARCH coefficient of 0.560865 indicates that Zimbabwean remittances are hyper-sensitive to news shocks, reacting immediately to domestic events such as currency introductions and to global shocks like the Russia-Ukraine conflict that spiked grain and fuel prices. Yet the remarkably low GARCH coefficient of 0.006961 suggests these shocks lack a long memory: volatility decays quickly once a new normal is established. With a combined persistence of 0.561, the system remains stable in the long run, but the authors argue it stays trapped in a cycle of policy-induced volatility in which constant short-term fluctuation prevents remittances from maturing into stable investment capital.

These findings complicate the conventional counter-cyclical view of remittances as reliable safety nets that rise whenever home conditions deteriorate. The authors contend that remittances’ overall impact depends on how they are used, proposing a pro-cyclical pattern in developing countries with high private investment during domestic uncertainty and a counter-cyclical pattern in areas with inadequate public services. In Zimbabwe’s case, the Income Stabilization Hypothesis explains why funds flow at all, with the diaspora acting as private insurance during droughts and inflationary squeezes, while the uncertainty results explain the channel choice: remitters stabilize household income but bypass formal banking to shield money from what the authors describe as potential currency expropriation.

The study also carries a dependency warning. With remittances making up a sizable portion of Zimbabwe’s foreign exchange inflows, the economy remains highly vulnerable to external shocks such as tighter immigration regulations or downturns in major host countries including the United Kingdom and South Africa. The authors note this reliance may unintentionally encourage moral hazard at the policy level, reducing pressure on the government to execute the structural changes needed to revive the industrial sector. Among the paper’s recommendations are a legally binding Remittance Protection Act prohibiting forced conversion of foreign currency accounts, ring-fenced asset-backed diaspora bonds tied to income-generating infrastructure projects, and a targeted waiver of Zimbabwe’s 2 percent intermediated money transfer tax on digital remittance receipts to shift flows away from informal cross-border bus channels.

Several caveats deserve emphasis. The estimation window ends in 2019, so the COVID-19 pandemic, the 2024 ZiG currency launch and subsequent global shocks fall outside the fitted model, even though the authors discuss them as context. The uncertainty index is derived from a single text-mined source, and annual data limit the ability to capture within-year dynamics that the volatility findings hint at. The authors also acknowledge a significant gap in the empirical literature on how economic uncertainty affects remittance movements, noting that prior panel studies of major African recipients using GMM estimation found no contemporaneous relationship between remittances and economic policy uncertainty.

Subject of Research: A time-series study of how economic uncertainty, inflation and GDP shape remittance inflows and volatility in Zimbabwe from 2000 to 2019.

Article Title: A nexus between remittances and uncertainty in Zimbabwe

Article References: Kondo, T., Mutsvangwa, S., & Manzote, E. (2026). A nexus between remittances and uncertainty in Zimbabwe. Discover Analytics, 4(1), Article 36. https://doi.org/10.1007/s44257-026-00085-2

Image Credits: AI Generated

DOI: 10.1007/s44257-026-00085-2

Keywords: Zimbabwe, remittances, economic uncertainty, ARDL model, GARCH, inflation, diaspora, macroeconomics, informal channels, time-series analysis, nexus, between