Error Correction Model Research Articles

Measuring the Relationship Between Oil Revenues and the Parallel Exchange Rate in Iraq for the Period (2003-2023): An Empirical Study

This study is an empirical investigation into the relationship between oil revenues and the parallel exchange rate in Iraq during the period from 2003 to 2023, highlighting the susceptibilities of a rentier economy dependent overwhelmingly on oil exports. The study adopted a deductive procedure coupled with econometric analysis using the Autoregressive Distributed Lag (ARDL) method to analyze the impacts of oil revenues and GDP without oil on the parallel exchange rate. Annual data were gathered from official Iraqi agencies and subjected to unit root tests, bounds cointegration tests, and error correction model (ECM) tests. The results indicate a statistically significant long-term negative relation between oil revenues and the parallel exchange rate, meaning that as oil revenues increase, the exchange rate appreciates. In the same vein, GDP without oil was also found to exert a negative influence on the parallel exchange rate, illustrating how the non-oil sector is crucial to the stabilization of the economy. Describing how fluctuations in oil revenues induced exchange rate dynamics, the results also accentuated the need for exchange rate stabilization through diversification and sound oil revenue management. These inferences are instructive for policymakers who endeavor to stabilize the exchange rate and promote sustainable economic development in resource-dependent economies like Iraq.

Cointegration between Southeast Asian and global equity markets

This study examines the financial cointegration between Southeast Asian stock markets—namely Vietnam, Thailand, the Philippines, Malaysia, Indonesia, and Singapore—and major global markets including the United States, United Kingdom, Germany, Japan, and China over the period from January 2009 to December 2023. The rationale for this research lies in the critical importance of understanding the extent of financial integration, which has significant implications for regional economic stability, cross-border investment strategies, and the formulation of effective financial policies. Employing the bounds testing approach for cointegration alongside an error-correction model (ECM) within the Autoregressive Distributed Lag (ARDL) framework, the analysis reveals robust short-term and long-term linkages between Southeast Asian and global stock markets. Of particular note is the strong and statistically significant integration with the Chinese stock market, highlighting China’s growing influence in the regional financial architecture. The findings underscore the necessity for investors to incorporate global market dynamics, especially those of China, into portfolio diversification decisions, while policymakers are advised to enhance regulatory measures to mitigate potential risks arising from global market shocks. This study thus offers valuable insights for advancing financial market development and stability in Southeast Asia amid increasing globalization.

A natural language processing (NLP) approach for optical character recognition (OCR)-resilient extraction, correction, and structuring of karyotype data in oncology clinical notes.

e13644 Background: Cytogenetics drives precision oncology by uncovering genetic abnormalities that contribute to cancers. Karyotypes, essential for cytogenetic analysis, are documented in the International System for Human Cytogenetic Nomenclature (ISCN) and prevalent in various free-text clinical documents, posing challenges for manual abstraction and computational processing. Furthermore, OCR technology used to digitize these documents often introduces errors and compromises the secondary use of health data, especially problematic for ISCN notation where a single character change can alter meaning. In response, we present a novel NLP approach to extract and structure karyotype data from clinical notes using automated OCR error correction. Methods: We developed a cancer-type-agnostic NLP pipeline by training two semi-supervised models on randomly sampled clinical notes (> 85% from oncology patients, including breast, lung and hematopoietic cancers) in the Tempus Database (Tempus AI, Inc., Chicago, IL): a named entity recognition (NER) model to identify karyotype strings in ISCN notation and T5, a transformer–based model for OCR error correction in identified karyotypes. We employed a two-tiered fine-tuning on T5 for training OCR error correction to reduce the need for manual curation: first on a public karyotype database with synthetic OCR errors, then on real OCR errors from clinical notes. The pipeline then standardized and structured the karyotype string into an in-house common data model. NLP model performances were evaluated against Gemma-2-27b, a state-of-the-art large language model, on curated labels from a mixture of clinical records. Results: The karyotype extraction model, trained as an NER task, achieved precision, recall, and F1 scores of 0.86, 0.92, and 0.90, respectively, on a test set of 2800 curated ISCN karyotype strings. Our fine-tuned T5 model significantly outperformed Gemma2, correcting 95% of synthetic OCR errors in a test set of 44,756 karyotype strings and 84% of real OCR errors from clinical notes in a test set of 2,790 karyotype strings, compared to Gemma-2’s 41% and 43%, respectively. Error analysis showed Gemma-2's tendency to edit uncommon but correct karyotypes to common ones and to inaccurately extend short karyotypes. Conclusions: To our knowledge, this is the first NLP-driven method for extracting and structuring karyotypes in clinical notes using fully automated OCR error correction irrespective of cancer type or document type. The model outperformed a state-of-the-art LLM in OCR error correction, accelerating the abstractions of cytogenetic information from clinical notes at scale. This advancement provides actionable cytogenetic information to oncology healthcare teams, enhancing the delivery of patient care.

IMPACT OF FOREIGN DIRECT INVESTMENT ON HUMAN DEVELOPMENT INDEX: A STUDY OF INDIAN ECONOMY.

Foreign Direct Investment (FDI) is widely recognized as a crucial catalyst for economic growth, while the Human Development Index (HDI) serves as a comprehensive measure of a nation's social and economic progress. Despite numerous studies investigating the connection between FDI, HDI, globalization, and other factors, the precise nature of the relationship between FDI and HDI remains somewhat unclear. This research paper aims to bridge this gap by empirically examining the impact of FDI on India's HDI score. Utilizing the time-series data from World Bank Indicators and the Handbook of Indian Economy spanning the period 1990-2022, the study employs the Autoregressive Distributed Lag (ARDL) model to analyze the long-run impact of FDI on HDI. Furthermore, Error Correction Model is employed to investigate the short-run relationships between these variables. The empirical findings indicated the existence of long-run and short-run relationship between FDI and HDI along with a positive response of both the variables to a shock (impulse) in the corresponding variable. These findings are expected to provide valuable insights to the extent to which FDI contributes to human development in India. By understanding the nature and strength of this relationship, policymakers can formulate more effective strategies to attract and leverage FDI for enhancing human development outcomes, including improving education, healthcare, and overall quality of life for Indian citizens.

Implications of Monetary Policy in Nepal’s Balance of Payment Trajectory

This study examines the implications of monetary policy on Nepal's balance of payments (BOP) using advanced time series techniques, including the Augmented Dickey-Fuller test, Johansen cointegration, Vector Error Correction Model (VECM), and Impulse Response Function (IRF) using data from 1975-2023 . The analysis explores the long- and short-run dynamics of monetary policy instruments—exchange rates, interest rates, money supply, and remittances—while accounting for structural breaks due to economic transitions, political instability, and external shocks. Key findings indicate a significant long-term equilibrium relationship among the variables, with exchange rate depreciation and higher interest rates adversely affecting the BOP, while money supply expansion exerts a positive influence. Notably, remittance inflows exhibit a counterintuitive negative relationship, suggesting inefficiencies in their utilization. The VECM results highlight a robust short-term adjustment mechanism, underscoring the role of exchange rate management and monetary policy in maintaining external stability. This research provides valuable insights into the interplay between monetary policy and the BOP, offering a framework for addressing economic challenges in a remittance-dependent, low-income economy like Nepal.

Factors Influencing Coffee Export Decisions: A Case Study of Vietnam

This paper explores the critical factors shaping coffee export decisions in Vietnam, one of the world’s largest coffee producers and exporters. Adopting a mixed-method approach that combines quantitative surveys with in-depth interviews involving coffee exporters and trade policymakers, the study identifies several key determinants including government trade policy, global coffee demand, production scale, supply chain infrastructure, and international pcoffee volatility. These variables collectively influence the strategic orientation of Vietnamese coffee exporters in the global marketplace. The findings offer valuable insights into how Vietnam can further enhance its export competitiveness and develop resilient, sustainable strategies for long-term growth in the coffee sector. Empirical evidence suggests that coffee production levels, yield per hectare, and global demand have a statistically significant and positive influence on export performance. Conversely, both domestic coffee pcoffees and international export pcoffees exhibit a negative relationship with export volume, indicating that elevated pcoffees may either constrain domestic supply or erode international pcoffee competitiveness. Interestingly, domestic consumption appears statistically insignificant in affecting export decisions, underscoring that Vietnamese coffee exports are predominantly shaped by supply-side capabilities and global market dynamics rather than internal demand pressures. To further analyze the short-run dynamics and the adjustment mechanism toward long-run export equilibrium, a Vector Error Correction Model (VECM) was estimated. The VECM results reveal that deviations from long-run equilibrium are corrected at a pace of approximately 0.62% per year, pointing to a slow but consistent realignment process in Vietnam’s coffee export system. In conclusion, the study recommends that Vietnamese policymakers prioritize increasing yield efficiency and expanding coffee production capacity, as these were found to be the most influential drivers of export growth. Moreover, strengthening access to global markets and implementing mechanisms to mitigate pcoffee fluctuations will be essential to reinforcing Vietnam’s competitive position in the international coffee trade.

Forestry and economic growth in Ghana: evaluating the dynamics using the environmental Kuznets curve and adjusted net savings

PurposeThis study investigates the link between economic growth, environmental sustainability and deforestation in Ghana, aiming to identify the economic drivers of deforestation and assess how sustainable economic practices can mitigate its rates.Design/methodology/approachThe study used secondary data from 1980 to 2023. It applied quantitative techniques, including regression, vector error correction model and multiple Granger causality to examine the impact of GDP growth, adjusted net savings (ANS) and other control variables on Ghana’s deforestation rate.FindingsThe analysis supports environmental Kuznets curve (EKC) hypothesis, indicating that deforestation initially rises with GDP but declines at higher levels. It finds a long-term relationship where economic growth correlates with reduced deforestation. ANS promotes sustainable growth, while FDI increases deforestation.Research limitations/implicationsThe study supports the EKC hypothesis, indicating that economic growth initially increases deforestation but that ANS positively impacts long-term GDP growth. It emphasizes directing FDI toward sustainable sectors to mitigate deforestation. Overall, integrating environmental sustainability into economic planning is crucial for Ghana’s growth.Practical implicationsTo support sustainable economic development in Ghana, policies should integrate environmental sustainability into growth strategies and standardize adjusted net savings as a metric for evaluating resource-intensive projects. Directing FDI toward sustainable industries, along with stabilizing inflation, can help mitigate deforestation while promoting eco-friendly practices.Originality/valueThis study’s originality lies in analyzing Ghana’s forestry and economic growth through the EKC framework and adjusted net savings from 1980 to 2023. Unlike prior research, this paper addresses overlooked interactions between growth, environmental sustainability, population growth and FDI using more recent, stable data relevant to current policy decisions.

Response of Macroeconomic Indicators to External Shocks in Indonesia

As a developing country with a high level of economic openness, Indonesia is classified as vulnerable to global economic dynamics. This study aims to analyze the response to external shocks, namely the COVID-19 pandemic, the Fed's interest rate increase, and USD/IDR exchange rate fluctuations on Indonesia's macroeconomic indicators, namely Gross Domestic Product (GDP) and Consumer Price Index (CPI), as well as evaluate the government's fiscal policy in responding to these pressures during the 2013–2023 period. The research used secondary data for the quarter 2013:Q1 and 2023:Q4, with as many as 44 observations of each variable, using the Vector Error Correction Model (VECM) method. The results of the estimate show that the USD/IDR exchange rate and the Fed's interest rate have a significant long-term relationship with Indonesia's real GDP and CPI. Throughout the research period, the government responded through various fiscal policies such as fuel subsidy adjustments (2013–2014), strengthening infrastructure and tax reform (2015–2019), large stimulus through the PEN program during the pandemic (2020–2022), and returning to fiscal discipline in 2023 with a focus on social protection, human resource development, and industrial downstreaming. These findings underscore the importance of adaptive fiscal policies in mitigating the impact of external shocks on the domestic economy.

Eggcellent Insights: Co-integration Analysis and Predictive Modeling across Production and Consumption Centers in India

Growing demand for poultry products has captured the attention of market aspects of poultry industry. In this dynamic market, how well the market functionaries are operating, to what extend the price transmissions are captured and delivered to the stakeholders and such queries are vividly explained by this study. The daily wholesale prices of major egg markets, comprising production and consumption centers listed by National Egg Coordination Committee web portal, for a period of 486 days were taken for the study. Johansen’s co-integration test was applied to identify whether the spatially separated markets are co-integrated or not. Post analysis of unit root test by Augmented Dickey Fuller statistic, it is evident that the selected egg markets are co-integrated in the long run. While in the short run dynamics, the Vector Error Correction Model (VECM) explains the price transmission and speed of price adjustment among the egg markets. Granger’s causality test showed bidirectional influence of price among selected markets. The currently evolving Long Short-Term Memory (LSTM) model revealed that the model is viable in performing the predictions of future egg prices, but it does not coincide with the National Egg Coordination Committee (NECC) depicted prices. Further improvements could be focused on the egg price prediction process; which ultimately benefits all the stakeholders in this agribusiness.

Estimating Labor and Total Factor Productivity in the Jordanian Agricultural Sector

This study investigates the Jordanian agricultural sector's labor productivity, technical efficiency, and total factor productivity from 1990 to 2023. It studies the interaction between agricultural output and the factors of production, including labor, capital, and land, while emphasizing the role of economic policy in maximizing output per unit of input. In terms of methodology, the study applied econometric models, including the growth accounting methodology and the vector error correction model (VECM) to analyze the long-run relationship and the data envelopment analysis (DEA) to measure technical efficiency. The results showed that labor productivity and total factor productivity (TFP) in the Jordanian agricultural sector went through three phases. The first was a noticeable decline in the 1990s, followed by an improvement during the period 2000–2011, and then a renewed slowdown after 2011, which was attributed to several factors, including a decline in agricultural investments, restrictions on foreign labor, and rising production costs. The VECM model results indicated a long-term relationship between agricultural output and each of capital, labor, and cultivated land, with labor showing greater importance than the other factors. On the other hand, the results of the DEA showed an improvement in technical efficiency up to 2011, followed by a decline due to the underutilization of economies of scale and weak resource use. The study recommends focusing on policies that support investment in agricultural technologies; It also recommends promoting local labor training and developing agricultural infrastructure to improve efficiency and achieve sustainable productivity growth.

The Role of Agriculture in Shaping CO2 in Saudi Arabia: A Comprehensive Analysis of Economic and Environmental Factors

This research examines the critical issue of greenhouse gas emissions, focusing on carbon dioxide (CO2) as a significant contributor to climate change and its threats to environmental sustainability. The primary objective of this paper is to highlight the environmental impacts resulting from economic growth, energy consumption, and agricultural development in Saudi Arabia. The purpose of the empirical research is to investigate the dynamic causal relationships between CO2 emissions, agricultural development, economic growth, energy consumption, and additional control variables in Saudi Arabia from 1990 to 2022. It is hypothesised that increases in agricultural land, economic activity, and energy use contribute to rising CO2 emissions. This study examines these relationships using the Autoregressive Distributed Lag (ARDL) and Fully Modified Ordinary Least Squares (FMOLS) methodologies, along with unit root tests, the ARDL bounds test, and Vector Error Correction Model (VECM) causality analysis, to assess both short-term and long-term interactions among the variables. The findings reveal that agricultural land expansion, economic growth, and energy consumption significantly contribute to increased CO2 emissions. Specifically, a 1% increase in agricultural land correlated with a 0.16% rise in CO2 emissions, while a 1% increase in economic growth and energy use led to 0.28% and 0.85% rises, respectively. These results underscore the environmental challenges posed by economic expansion and energy dependence. This paper emphasises the need for policies that balance economic growth with emissions reduction, in line with Saudi Vision 2030. Transitioning to a low-carbon, circular economy supported by renewable energy and innovation is essential for sustainable development and climate change mitigation.

DYNAMICS OF GOVERNMENT EXPENDITURE ON ECONOMIC SERVICES AND ECONOMIC GROWTH IN NIGERIA

The main objective of this research work is to evaluate the dynamics of government expenditure on economic services and economic growth in Nigeria between the period of 1996 and 2023. This has become important because despite the huge funds allocated for economic services in Nigeria, the impact of such had not been significantly felt on the level of economic growth. The regression analysis with special use of the Error Correction Model (ECM) were used to analyze the data. The findings revealed that a long run equilibrium relationship existed among the variables. The results also showed that the expenditure on economic services had a significant and positive impact on the level of economic growth in Nigeria. The expenditure on education also had positive and significant impact on the level of economic growth. On the basis of the above findings, more budgetary allocations to economic services and the educational sector, under proper supervision is therefore recommended amongst others.

Exploring the nexus between environmental degradation and living standard in Bangladesh: Evidence from ARDL and ECM technique

A nation’s ability to maintain a lower level of environmental degradation is considered pivotal for achieving a robust living standard. This study evaluates the short- and long-term effects of Bangladesh’s GDP, energy consumption (ENC), food production index (FPI), and life expectancy at birth (LEB) on CO2 emission using time series data over the period 1990–2021. In doing so, the study uses an Autoregressive Distributed Lag (ARDL) bounds testing model. The short-run disequilibrium behavior of the variables is also captured using the Error Correction Model (ECM). Then, the Granger causality test was applied to identify the causal relationship between variables. The outcome reveals a long-term relationship between variables. While ENC has a significant positive impact on CO2 emissions per capita, GDP per capita exhibits a significant negative impact. Additionally, if there is any departure from equilibrium, the rate of return to equilibrium is about 67.30%. The study also found a unidirectional causal relationship between CO2 emission per capita to GDP per capita and the bidirectional causal relationship between CO2 emission per capita and FPI. Building upon the obtained results, future efforts to promote living standards can be better achieved by matching the most suitable factors for their effective response to the environment. Therefore, the study suggests that the government should promote alternative energy sources like renewable energy, carbon pricing, energy-efficient technology, eco-friendly agricultural practices, higher economic growth, and life expectancy to reduce environmental deterioration and promote living standards simultaneously.

IMPACT OF MACROECONOMIC VARIABES ON THE PERFORMANCE OF THE NEPAL STOCK MARKET: EMPERICAL ANALYSIS USING THE VEC MODEL

The Stock Exchange plays a vital role for generating, investing, and growing the wealth and diversify portfolios. This study investigates the influence of macroeconomic variables on the Nepal Stock Exchange (NEPSE) performance, focusing on the lending interest rate (LIR), money supply (MS), and liquidity (LIQ). The objective of this research is to assess the long-run cointegration, evaluate the short-run dynamics and error correction, and conduct Granger causality tests to identify causal linkage. This study employs the vector error correction (VEC) model to analyze the determinants of the Nepal Stock Exchange (NEPSE) index from January 2005 to December 2024, utilizing 203 observations with the required lags. The study finds that there is a significant long-term relationship between NEPSE and MS, and a negative impact from liquidity. The results suggest that MS and LIQ exhibit significant effects on NEPSE, whereas LIR does not show a substantial long-term relationship. In the short-term, the study identifies weak short-term adjustments for LIR and LIQ but significant autoregressive effects for MS and NEPSE. Additionally, the Granger Causality Test reveals that money supply and liquidity have predictive power for NEPSE, with one-way causal relationships from MS and LIQ to NEPSE.

Factors affecting for sustainable improvement of palm oil industry in the world market: Ex-post forecast approach

Currently, there is significant political and economic dependence on the palm oil industry in Malaysia, Indonesia, and Thailand. They are the most significant world producers and exporters. The objective of this study is to investigate the factors affecting the sustainable improvement of world production, consumption, and price in the palm oil market. This study employed a vector error correction model (VECM) along with an ex-post forecast approach. The data used monthly data from January 2014 to December 2019, covering 72 observations of pre-COVID-19 periods for analysis purposes. The study found that there were significant long-term relationships among the variables representing palm oil consumption, world population, and soybean oil price for palm oil price. Additionally, there were short-term relationships among exchange rates, palm oil production, and consumption for price. Changes in world total palm oil production are based solely on changes in world palm oil price. Moreover, changes in world total palm oil consumption are also based on world population, soybean oil price, and changes in world palm oil price. In summary, companies and governments that proactively implement sustainable measures will be better positioned to navigate regulatory challenges, maintain market access, and ensure long-term industry stability.

Impact of Foreign Direct Investment on The Growth of Nigeria’s Economy: (A Case of the Manufacturing Sector 1980-2023)

This study examines the impact of Foreign Direct Investment (FDI) on the growth of Nigeria’s Economy: (A case of manufacturing sector between 1980-2023) using the Ordinary Least Squares method of estimation. Descriptive statistic, trend analysis, ADF unit root were initially prepared. It was indicated that all the variables were stationary at level and first difference I(0) and I(1). The Autoregressive Distributed Lag (ARDL) cointegration revealed that FDI has significant relationship with manufacturing output and inversely related (-2.02E-09) in short-run but positively related (0.00) in the long-run. Exchange rate (-0.04) was negatively related with manufacturing output in short-run but positively related in the long-run (0.19) Inflation rate (0.12) and (0.90) has positive impact of growth of Nigeria’s manufacturing output and statistically significant in the long-run. More so, capacity utilization rate (0.08) and (0.04) was insignificant both in short and long-run ARDL model reparameterized into Error Correction Model (ECM) revealed the long-run equilibrium was corrected in the current period at an adjustment speed of 62%, statistically significant and negatively signed. Based on the findings, it was recommended that the government ought to come up with more pleasant economic policies and business environment, which will attract FDI into virtually all the sectors of the economy. On the issue of corruption and diversion of funds from FDI inflows, agencies established to fight corruption such as Economic and Financial Crimes Commission and Independent Corrupt Practices Commission should be seen to do their jobs to convince both foreigners and nationals that Nigeria is safe for investment. There is need to encourage and accelerate the factors that affect productivity in the manufacturing sector of the country especially manpower and skills for as long as productivity is low, there cannot be a meaningful growth in the manufacturing sector.

Growth in motion: the effects of terms of trade components, labor, capital, and investment on U.S. economic performance

This study significantly contributes to the existing body of knowledge by examining the long- and short-run effects of terms of trade components (TOT computer & communication, TOT fuel, TOT food, and TOT goods), capital, labour force, stock trade, and investment on U.S. economic growth from 1980 to 2021 using the Autoregressive Distributed Lag (ARDL) model. The findings of terms of trade (TOT) reveal that TOT computer & communication and TOT food are primarily export-oriented components, whereas TOT fuel and TOT goods are predominantly import-oriented components. However, the findings of the unit root test reveal that all variables are stationary at the first difference I(1). The ARDL bounds test confirms the existence of a long-run relationship between the dependent and independent variables. Long-run analysis indicates that TOT fuel and TOT food negatively affect economic growth, while TOT goods and TOT computers & communication positively contribute to it. Additionally, capital, labour force, and investment are found to be key drivers of U.S. economic growth. The Error Correction Model (ECM) results show an 87% adjustment rate from short-run to long-run equilibrium, signifying a gradual convergence toward equilibrium. The time-varying Granger Causality test demonstrates that GDP causally impacts terms of trade in computer and communication products, goods, labour force, gross capital, and stock trade. Furthermore, impulse response analysis reveals a stable and positive upward trend in GDP's effect on TOT goods, TOT computer & communication, and TOT food, while TOT fuel exhibits a downward trend. The study recommends that policymakers invest in the technological sector to reduce reliance on fuel imports, enhance international trade, and thereby promote sustained economic growth.

Analysis of stock liquidity in banking development: Evidence from Bank Jago

This study is based on the development of digital banks that have begun to increase along with the emergence of many digital banks and the increase in the value of digital bank transactions since the Covid-19 pandemic in Indonesia. This study aims to determine the growth pattern of Bank Jago's success which causes several factors to influence stock liquidity, namely company value, stock trading volume and stock trading frequency. The analysis method used is VECM (Vector Error Correction Model), a statistical technique that captures both short-term and long-term dynamics in a system of variables, making it particularly suitable for studying stock liquidity. The data used is monthly data with a time span from January 2020 to December 2023. The results of the VECM estimation test show that the variables of company value, stock trading volume and stock trading frequency have an effect on stock liquidity in the long-run due to the emergence of speculation that digital banks have positive prospects during the Covid-19 pandemic which caused an increase in Bank Jago shares from various aspects and had no effect in the short term due to a decline in investor views and company performance in the period at the end of 2022. The implication of this study can be used to formulate strategies to increase stock liquidity at Bank Jago and can be implemented in other digital banks.

Impact of climate and economic policy uncertainties on inflation in India: using the vector error correction model approach

Impact of climate and economic policy uncertainties on inflation in India: using the vector error correction model approach

Organic food consumption dynamics in Germany during economic crises

This study investigates the effects of the 2008 global economic crisis and the 2020 COVID-19 pandemic on organic food consumption in Germany, the largest organic market in Europe. Specifically, it examines (1) the relationship between Gross Domestic Product (GDP) and organic food consumption during crisis and non-crisis periods (disposable income is also employed as an alternative measure instead of GDP to verify the stability of the results), (2) the presence of a long-term equilibrium between these variables, (3) the short-term dynamics governing the adjustment toward this equilibrium, and (4) the differences in these dynamics under stable economic conditions and crisis periods. To analyze these relationships, the study employs an Error Correction Model (ECM) with Markov Regime Switching (MRS) and Threshold Cointegration Methodology (TCM), as both modeling frameworks allow for the identification of structural changes in the data. The findings indicate a significant dependence of organic food consumption on GDP (income), but only in non-crisis periods. While a long-term equilibrium relationship between GDP (income) and organic food consumption is confirmed, the adjustment mechanism toward this equilibrium varies considerably between economic stability and crisis periods.