The research, published in Frontiers in Sustainable Food Systems, assembles a balanced panel of 3,672 country-month observations spanning Latin America, Asia, and the Europe-Middle East-Africa region. Countries were selected using strict criteria: they had to be classified as emerging markets by MSCI or the International Monetary Fund, operate floating rather than pegged exchange rate arrangements, avoid centrally administered food prices, and offer complete monthly data. Crucially, none of the selection rules conditioned on realized inflation behavior, which guards against the sample being rigged in favor of the study’s conclusions.

The methodological architecture is deliberately layered. In the first stage, Unuvar estimates a separate distributed lag regression for each country, regressing monthly food inflation on twelve lags of currency depreciation alongside six lags of Brent crude oil prices, the FAO Food Price Index, and urea fertilizer prices. Standard errors use the Newey-West correction for heteroskedasticity and autocorrelation up to twelve months. This country-by-country approach is not a stylistic choice: formal tests rejected slope homogeneity across the panel, and because global price series take identical values in every country each month, they would be perfectly collinear with time fixed effects in any pooled specification. Only country-level regressions allow the oil, food, and fertilizer channels to be separately identified.

The headline numbers are striking. The mean cumulative exchange rate pass-through coefficient is 0.213, meaning a ten percent currency depreciation over twelve months raises consumer food prices by roughly 2.1 percent on average. But the mean conceals extraordinary heterogeneity: estimates range from essentially zero in Indonesia to 0.807 in Türkiye, where pass-through is nearly four times the group average. Hungary follows at 0.505, with Chile and Colombia near 0.34. Only seven of the seventeen coefficients are individually significant at the five percent level, a reminder that any study reporting a single pooled elasticity for emerging markets describes a central tendency that applies to very few actual economies.

By contrast, the oil channel is remarkably weak at policy-relevant horizons. The cumulative effect of crude oil prices on consumer food prices is just 0.008 over six months — statistically indistinguishable from zero — and the entire oil-only specification explains roughly 0.4 percent of within-country variation in food inflation. The effect does become detectable at longer horizons, reaching 0.045 at twelve months and 0.064 at eighteen months, suggesting that energy costs seep into retail prices slowly through production and distribution. But the comparison remains lopsided: a ten percent oil price increase is associated with about a 0.5 percent rise in food prices, versus roughly 2.4 percent for an equivalent depreciation. A formal test rejects the equality of the two channels decisively.

Why is the energy-food nexus so muted at the consumer level? The study points to the structure of retail food prices, which bundle the raw commodity with processing, packaging, distribution, rent, and labor costs. In the United States, the farm share of the consumer food dollar was just 11.8 cents in 2024, with energy entering as one of twelve supply-chain industry groups rather than a dominant cost. Strong oil-commodity relationships observed at the wholesale level are therefore diluted before they reach the checkout. The exchange rate, by contrast, hits from multiple directions simultaneously: it raises the local-currency cost of imported fertilizers, seeds, and fuel, while also lifting the domestic prices of tradable agricultural goods outright.

The study’s most consequential finding concerns state dependence — the idea, originating with John Taylor’s 2000 work, that pass-through is not a fixed structural parameter but depends on the prevailing inflation environment. When inflation is low and expectations are anchored, firms treat cost shocks as temporary and absorb them into margins. When inflation is perceived as persistent, the same shock is passed through rapidly and almost entirely. Using a threshold specification based on observed twelve-month food inflation, the study finds cumulative pass-through of 0.147 below a fifteen percent annual inflation threshold and 0.541 above it — a difference of 0.393 that survives a Bonferroni correction for multiple testing. In practical terms, a ten percent depreciation raises food prices by about 1.5 percent in calm conditions but by approximately 5.4 percent when food inflation is already elevated.

Formal threshold estimation sharpens the picture. Applying Hansen’s panel threshold method, the transition point is estimated at 7.56 percent annual food inflation using overlapping six-month windows, and 6.83 percent with non-overlapping windows, with bootstrap p-values below 0.001 in both cases. Pass-through roughly triples across this divide, rising from about 0.07 to 0.23. Quantile regressions with country fixed effects corroborate the pattern from a different angle: cumulative pass-through climbs from 0.120 at the twenty-fifth percentile of the conditional food inflation distribution to 0.277 at the ninetieth, with equality strongly rejected. Notably, the oil and global food price channels show no comparable regime dependence, suggesting the state-dependent behavior is specific to the exchange rate transmission mechanism.

A skeptic might object that the high-inflation states are simply concentrated in countries with structurally stronger pass-through, such as Türkiye, rather than reflecting a within-country behavioral shift. The study confronts this directly with mean-group estimates that compare inflation states within each economy. The estimated difference is positive in all eight economies where both states can be reliably estimated, and the mean-group difference of 0.339 remains significant even after excluding Türkiye, which contributes fifty-five of the 190 high-inflation months. Kazakhstan, Romania, and Poland — countries with modest average pass-through — show some of the largest state-dependent jumps. Meanwhile, structural exposure indicators such as food import dependence, energy dependence, and fertilizer import dependence fail to explain cross-country variation, with the apparent link between average inflation and pass-through collapsing entirely once Türkiye is removed from the cross-section.

The policy implications are pointed. If exchange rate transmission is the dominant channel, then export bans and trade restrictions are misguided levers: they depress producer incomes and risk supply contractions without touching the mechanism that actually drives prices. Instead, the findings elevate macro-financial stability — exchange rate stability, anchored inflation expectations, and hedging instruments for importers — to the center of food price policy, with agricultural subsidies playing only a complementary role. The results also align with the United Nations Sustainable Development Goal 2.c, which targets the proper functioning of food markets and limits on extreme price volatility. As the study notes, regime dependence intensified after 2015, a period encompassing emerging market currency stress, the pandemic, and the war in Ukraine, hinting that weakening monetary credibility may itself amplify the food price consequences of currency turmoil. For the billions of households in emerging economies who spend a disproportionate share of their budgets on food, keeping inflation anchored may be the most effective food security program available.

Subject of Research: Exchange rate pass-through to consumer food prices and its threshold dependence on the inflation environment in emerging market economies

Article Title: Threshold effects in exchange rate pass-through to food prices in emerging market economies

Article References: Unuvar, F. I. (2026). Threshold effects in exchange rate pass-through to food prices in emerging market economies. Frontiers in Sustainable Food Systems, 10, Article 1960606. https://doi.org/10.3389/fsufs.2026.1960606

Image Credits: AI Generated

DOI: 10.3389/fsufs.2026.1960606

Keywords: exchange rate pass-through, food inflation, emerging market economies, oil prices, threshold effects, state dependence, food security, currency depreciation, Taylor hypothesis, quantile regression, panel data, monetary policy

The numbers behind that argument are stark. The Strait of Hormuz, the narrow maritime chokepoint through which roughly a fifth of the world’s oil supply passes, has been repeatedly disrupted, constraining hydrocarbon exports and sending crude prices from around $70 to more than $110 per barrel by March 2026, before easing back to around $80 in July as the market absorbed the volatility. According to the analysis, attacks on shipping in the strait have curtailed up to 20 million barrels per day of exports, generating substantial daily revenue losses for producing states. For consumers, the same disruption translated into higher petrol, diesel and jet fuel prices; for producers, it meant a paradoxical combination of elevated prices and collapsing export volumes.

Iran’s response to Israeli and American strikes on military, nuclear and some energy facilities included attacks on targets across the region, among them energy infrastructure within the Gulf Cooperation Council states. The analysis documents physical damage and, in some cases, temporary suspensions at key sites such as Ruwais in the United Arab Emirates, Ras Tanura in Saudi Arabia, Bapco Energies in Bahrain and Mina Al-Ahmadi in Kuwait, alongside disruptions to Qatari liquefied natural gas production. These are not marginal facilities. They anchor the export capacity of some of the largest hydrocarbon producers on Earth, and their vulnerability exposed a structural weakness at the heart of the Gulf’s economic model.

That weakness, as Bayoumi and Mason frame it, is a circular dependency. For years, Gulf states, particularly Saudi Arabia and the UAE, have invested heavily in renewable and clean energy as part of broader economic diversification strategies. But the hydrocarbon revenues that fund that diversification are precisely the revenues most exposed to geopolitical disruption. Despite elevated oil prices, revenue losses, rising defence expenditure and inflationary pressures are weighing on gross domestic product, national budgets and planned investments across the region. The severity of the impact depends on how long the conflict lasts, but a prolonged disruption could force governments to reprioritise, potentially squeezing the very clean energy programmes designed to reduce their dependence on oil income.

The authors place the 2026 conflict in a longer historical pattern of energy shocks driving policy change. The oil crises of the 1970s and the 1979 Iranian revolution quadrupled prices and pushed the United States to expand fossil fuel production, including opening new fields in Alaska and loosening drilling regulations. The price surge of the early 2000s led many oil-importing countries to subsidise fuel prices while the US and Canada expanded output. More recently, the Russia-Ukraine war prompted the European Union to diversify its energy sources and increase investment in renewables through its REPowerEU programme. Each shock, in other words, produces a short-term scramble for supply followed by a longer-term restructuring of the energy system.

What distinguishes the current moment, the analysis argues, is the revelation of a persistent policy failure: governments continue to treat energy security primarily as a supply problem rather than a demand-side transformation challenge. The distinction matters technically. Supply-side responses, stockpiling, diversifying suppliers, subsidising fuel, leave economies exposed to the next disruption because demand for globally traded fuels remains intact. Demand-side transformation, by contrast, reduces the volume of traded fuel an economy needs in the first place, through efficiency, electrification of transport and heating, and deployment of domestic renewable generation whose fuel cost is zero and whose supply chain is local. Repeated geopolitical shocks strengthen the strategic case for exactly that approach.

The differential outcomes among importing economies illustrate the point. China has fared better than many East Asian economies thanks to strategic stockpiles and more resilient supply chains, and its firms hold dominant positions in solar photovoltaics and electric vehicle manufacturing, positioning them to benefit if sustained high oil prices accelerate global electrification. In the European Union, natural gas prices have risen more than 70 percent and refined products such as jet fuel have experienced extreme price volatility, prompting the bloc to tell member states to prepare for prolonged disruption. Europe, already reshaping its energy system after the war in Ukraine, has diversified gas supplies across Norway, Qatar, Algeria and, at reduced levels, Russia, with Azerbaijan emerging as an additional supplier, while oil imports are spread across the United States, Norway, Kazakhstan and Middle Eastern producers.

Yet the transition is not a zero-sum contest between West and East. Cross-border clean energy investment has become a central pillar of energy security in its own right. The UAE’s Masdar and France’s TotalEnergies operate an approximately $2.2 billion joint venture across Asia, combining capital and technology. Saudi Arabia’s ACWA Power is partnering with European firms to export solar electricity and develop transmission links, while hydrogen projects such as the Yanbu green hydrogen project aim to supply European markets, with similar initiatives underway in the UAE and Oman. Gulf funds and firms have already financed multi-gigawatt solar projects in emerging markets, especially in Africa and Asia, and the UAE is leading cooperation with a South Korean KEPCO consortium on nuclear power. These partnerships suggest that the clean energy economy is being built through networks of interdependence rather than blocs of exclusion.

In the near term, the authors expect governments to respond to price shocks in familiar ways: subsidising fossil fuels, rationing, promoting remote working and demand-reduction measures, and in some cases reverting to more carbon-intensive options such as coal. Such measures echo past crises and may temporarily raise emissions. But over the longer term, the logic of energy security points in the opposite direction. Reducing dependence on globally traded fuels, not merely diversifying their sources, will be critical, the analysis argues, and governments that shift to clean technologies will benefit from adoption curves already driven by falling costs and rapid innovation. Recent research on electric vehicles has even identified evidence of a cascading positive tipping point, in which growing uptake reinforces itself through infrastructure, consumer expectations and manufacturing scale.

The central lesson the authors draw is that electrification and clean power are no longer just climate strategies but instruments of economic resilience and national security. Countries that move fastest will not only reduce emissions but also insulate themselves from future geopolitical shocks, whether those shocks come from a strait closed by war, a pipeline sabotaged, or a supplier weaponising exports. The 2026 Iran war, in this reading, is less a detour on the road to decarbonisation than a demonstration of why the road exists at all: an energy system built on concentrated, contested, globally traded fuels will remain a strategic liability, and every crisis makes that liability harder to ignore.

Subject of Research: The impact of the 2026 Iran war and Gulf energy infrastructure disruption on global energy security and the clean energy transition

Article Title: Conflicts and energy transitions: The case of the 2026 Iran War

Article References: Bayoumi, M., & Mason, R. (2026). Conflicts and energy transitions: The case of the 2026 Iran War. PLOS Sustainability and Transformation, 5(8), e0000265. https://doi.org/10.1371/journal.pstr.0000265

Image Credits: AI Generated

DOI: 10.1371/journal.pstr.0000265

Keywords: energy transition, energy security, Iran war, Strait of Hormuz, Gulf Cooperation Council, renewable energy, electrification, oil prices, geopolitics, Masdar, ACWA Power, PLOS Sustainability and Transformation

The methodological architecture of the study is what gives its findings their weight. Rather than relying on a single regression model, Salami combines Ordinary Least Squares estimation with Newey–West heteroskedasticity and autocorrelation-consistent standard errors, a correction that ensures the statistical conclusions remain robust even when the data exhibit the volatility typical of developing economies. On top of this baseline, the analysis layers time-series threshold regression, which allows the inflation–growth relationship to shift abruptly at a critical value, and smooth transition regression, which instead models a gradual change in the relationship as inflation rises. The two approaches are complementary: threshold models capture sharp regime changes, while smooth transition models capture softer, more continuous adjustments. Comparing their results provides a way to test whether the inflation–growth link truly behaves differently at different levels of inflation, or whether any apparent shift is a statistical artifact.

The headline result is that inflation is negatively and statistically significantly associated with real GDP growth in Nigeria, and that the magnitude of this association varies across inflation regimes. The threshold model identifies the critical value at 12.22 percent, and, notably, the inflation coefficient is negative both below and above that line. This is an important nuance. Some countries exhibit a benign zone of low inflation where the relationship is positive or neutral, turning negative only at higher rates. In Nigeria’s case, the data suggest that inflation is already a burden even at moderate levels, and that crossing the 12.22 percent mark changes the intensity of the damage rather than its direction. For a country that has experienced inflation rates well into double digits in recent years, this finding implies that the economy has been operating on the wrong side of the threshold for extended periods.

Rigorous science demands sensitivity analysis, and the study delivers one that addresses a subtle data problem. The trade-openness series used in the analysis required a completion procedure for its three boundary observations, and any such imputation could in principle distort the estimated threshold. To check this, the author re-estimated the model excluding those three boundary observations. The result was reassuring: the 12.22 percent threshold survived intact, and the regime-specific coefficients were closely comparable to the baseline estimates. This means the central finding is not materially driven by the data-completion procedure, a conclusion that substantially strengthens confidence in the threshold estimate. In empirical macroeconomics, where results can hinge on small sample choices, this kind of robustness check is the difference between a suggestive correlation and a defensible policy benchmark.

The smooth transition model tells a more cautious story. It identifies a transition location of approximately 11.50 percent, remarkably close to the threshold estimate, but its transition parameters are not statistically significant. In practical terms, this means the evidence for a gradual, smooth adjustment of the inflation–growth relationship is weaker than the evidence for a discrete regime shift. The convergence of the two models on a similar location, around 11.5 to 12.2 percent, is itself informative, suggesting that something real happens to Nigerian growth dynamics as inflation approaches the low teens. But the statistical weakness of the transition parameters means the threshold model remains the more reliable guide, and policymakers should treat the smooth transition results as corroborating rather than independently conclusive.

Inflation does not operate in a vacuum, and the study’s treatment of Nigeria’s external and fiscal environment is one of its most valuable contributions. Exchange-rate depreciation and international Brent crude oil-price shocks are both negatively associated with growth in the baseline specification, a result that reflects Nigeria’s well-known vulnerabilities as an oil-dependent economy with a currency sensitive to external pressures. Intriguingly, however, the independent statistical significance of these external variables weakens once nonlinear inflation dynamics are incorporated into the model. This suggests that part of the damage inflicted by oil shocks and currency depreciation may operate through their effect on inflation itself, which then transmits to growth. In other words, inflation may be the channel through which Nigeria’s external shocks do much of their harm, making price stability not merely one policy goal among many but a central defensive mechanism.

Perhaps the most policy-relevant finding concerns the interaction between inflation and fiscal conditions. The study finds a positive and statistically significant interaction between inflation and the fiscal balance, indicating that improved fiscal positions can attenuate, though not eliminate, the adverse association between inflation and growth. The mechanism is intuitive: when a government’s budget is healthier, it is better able to cushion households and firms against price shocks, avoid inflationary deficit financing, and maintain public investment that supports productive capacity. The crucial caveat is the word attenuate. Sound fiscal management softens the blow of inflation but cannot substitute for monetary control of prices. The finding underscores the study’s overarching conclusion that Nigeria’s growth stability depends on coordinated monetary, fiscal, and exchange-rate policies rather than on any single lever pulled in isolation.

The temporal dimension of the analysis reveals how Nigeria’s macroeconomic history is written into the data. Structural-break tests identify breaks in 2016, 2020, and 2023, corresponding to the country’s recession, the COVID-19-related economic disruption, and the exchange-rate liberalisation reforms respectively. These are not abstract statistical artifacts but recognizable chapters in Nigeria’s recent economic narrative. The 2016 recession followed the collapse of oil prices and foreign-exchange shortages; the 2020 break captures the pandemic’s simultaneous supply and demand shocks; and the 2023 break reflects the liberalisation measures that reshaped the currency regime. That the econometric tests independently detect these episodes lends credibility to the modeling framework, while also reminding analysts that parameter stability cannot be assumed in an economy subject to such repeated structural upheaval.

Complementary evidence comes from quantile regression, which examines how the inflation–growth relationship varies across the distribution of growth outcomes rather than only at the mean, and from machine-learning techniques applied in an explicitly exploratory role. Random Forest and XGBoost models were assessed using chronologically ordered hold-out validation, a demanding test that trains models on earlier data and evaluates them on later periods. The results indicated limited temporal generalisation, meaning the machine-learning models struggled to predict growth in unseen future periods. Consequently, their feature-importance and SHAP outputs are interpreted as exploratory nonlinear evidence rather than independent predictive or causal confirmation. This is a methodologically honest stance. Machine-learning tools can reveal complex interaction patterns that linear models miss, but without demonstrated out-of-sample predictive power, their outputs cannot be elevated to causal claims. The study’s willingness to constrain its own machine-learning findings is a model of restraint in a field often tempted by algorithmic overreach.

Taken together, the findings paint a coherent and sobering picture of Nigeria’s post-shock macroeconomic environment. The inflation–growth relationship is negative, regime-sensitive, and conditioned by fiscal and external circumstances. Trade openness is positively associated with growth, offering a rare bright spot, while broad money growth exhibits a negative baseline relationship, though these effects vary across specifications. Parameter-stability diagnostics, including CUSUM and CUSUMSQ tests, confirm that the baseline model’s coefficients and residual variance remain within statistical bounds, indicating no systematic instability that would undermine the estimates. For Nigerian policymakers, the practical message is clear: keeping inflation below the estimated 12.22 percent threshold, strengthening fiscal balances to buffer the inflation–growth nexus, and managing exchange-rate and oil-price exposures through coordinated policy are not competing objectives but interlocking requirements. For economists studying other emerging economies, the study offers a template for combining classical threshold econometrics with modern machine-learning diagnostics while respecting the limits of each. As global inflation pressures persist, the Nigerian experience serves as a reminder that the cost of letting prices drift upward is not abstract; it is measured in forgone growth, and the price of that mistake becomes steeper with every percentage point past the line.

Subject of Research: The nonlinear threshold relationship between inflation and economic growth in Nigeria

Article Title: Inflation threshold, fiscal conditions and growth stability in Nigeria’s post-shock macroeconomic environment

Article References: Salami, R. A. (2026). Inflation threshold, fiscal conditions and growth stability in Nigeria’s post-shock macroeconomic environment. Discover Sustainability. https://doi.org/10.1007/s43621-026-04682-9

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04682-9

Keywords: inflation, economic growth, Nigeria, inflation threshold, fiscal balance, exchange rate, oil prices, threshold regression, quantile regression, machine learning, macroeconomics, structural breaks