Inflation Rate Research Articles

Effect of Public Finance Implications on The Economic Standard of Nigerians: A Longitudinal Study

This study examined the impact of the national budget, exchange rates, trade openness, inflation rates, and interest rates on the purchasing power parity and per capita income of Nigeria during the period spanning from 2009 to 2022. Data was gathered from the Central Bank Nigeria and the World Bank. The data was further analyzed using descriptive statistics and Ordinary Least Square methods at a significance level of 5% for the purpose of detailed estimation. Results of the study showed that the national budget, exchange rates, trade openness, inflation rates, and interest rates had significant and positive impacts on Nigeria’s purchasing power parity and per capita income. The results of the study imply that, to increase the purchasing power parity and per capita income of Nigerian citizens, the government should focus on improving the quality of budget execution, ensure exchange rate stability, implement more trade policies that will open the Nigerian market and increase foreign investment, focus on maintaining a low inflation rate, and ensure the stability of

The public debt sustainability and its determinants in Sub-Sahara African countries

PurposeThis paper aims to answer the following important questions: Is public debt in Sub-Saharan African (SSA) countries sustainable? What are the determinants of public debt sustainability in these countries, and do these determinants exhibit heterogeneity due to regional, natural resource, and income differences among SSA countries?Design/methodology/approachThis study analyzes the public debt sustainability in SSA countries using the theoretical model known as the Present Value Budget Constraint (PVBC) model developed by Hamilton and Flavin (1986), and adopts the econometric testing method proposed by Trehan and Walsh (1991). Moreover, to empirically investigate the determinants of public debt sustainability in SSA countries, the System-Generalized Method of Moments (System-GMM) method is applied. Furthermore, this study conducts heterogeneity analysis by categorizing the sample based on different regions, natural resource endowments, and income levels. The data of this study are sourced from the IMF and World Bank databases for 45 SSA countries from 2005 to 2021.FindingsFindings reveal that public debt in SSA countries is not sustainable in the long run, with factors such as the previous government debt, long-term debt ratio, debt repayment capacity, economic growth rate, inflation rate, export to GDP, and government fiscal deficit rate influencing sustainability. Additionally, the factors exhibit heterogeneity attributed to regional, natural resource, and income variations among SSA countries.Practical implicationsThe findings of our study will serve as a catalyst for policymakers in the SSA countries to embrace and sustain robust fiscal consolidation and debt stabilization measures. Moreover, countries with distinct characteristics should implement tailored approaches. Additionally, policymakers in SSA countries should implement economic measures to address public debt issues. These measures include improving the macroeconomic structure, promoting economic transformation and diversification of industries, fostering sustainable economic growth, ensuring price stability, and strengthening resilience against external shocks and debt risks. Specifically, countries endowed with indigenous species, resources, and tourism potential should adopt a well-coordinated strategy that utilizes agriculture, tourism, ecotourism, and the hospitality industry as instruments for sustainable local community and rural development.Originality/valueFirstly, it assesses the sustainability of public debt and its determinants for countries in SSA, which distinguishes it from previous studies that only focus on either debt sustainability or determinants of debt separately. Secondly, by including multiple SSA countries in the analysis, this study stands out from prior research that predominantly concentrates on specific nations. Thirdly, the utilization of the System-GMM method for analyzing determinants adds a novel dimension to this study, departing from earlier literature primarily focused on debt thresholds. Lastly, the heterogeneity analysis conducted in this study provides an empirical foundation for tailoring policies to different countries, addressing a facet often overlooked in earlier literature.

A Factor‐Augmented New Keynesian Phillips Curve for the European Union Countries

AbstractIn this paper, a factor‐augmented version of the New Keynesian Phillips curve (NKPC) is assessed using a data set comprised of a large panel of European Union (EU) member countries. The factor‐augmentation is natural given that country‐level inflation rates are highly co‐moving. The presence of unattended common factors is important because it raises the issue of omitted variables bias, as the real marginal cost, which is a regressor of the NKPC, is likely to load on the same factors as inflation. One possibility here is to employ the regular instrumental variables approach. However, if the external instruments load on the same factors as the error term of the NKPC, the instruments would be invalid and the results would therefore likely be misleading. Motivated by this last observation, the present paper proposes a new estimator of the NKPC that allows for very general forms of factor dependencies and endogeneity. Our results provide evidence in support of the NKPC, but only after the presence of common factors has been appropriately accounted for.

Monetary Policy, Digitalisation and Banking Industry Performance in Nigeria

In the evolving financial landscape of Nigeria, the interplay between monetary policy and digitalization significantly influences the performance metrics of banks. This study explores the multifaceted impact of these two critical factors on the Nigerian banking sector. Monetary policy, orchestrated by the Central Bank of Nigeria, regulates the economy's money supply, affecting banks' lending behaviors and liquidity. Digitalization, on the other hand, offers a transformative potential for banks to enhance operational efficiency, customer experience, and service delivery through technological advancements. The study examines how money supply, lending rate and digitalization (proxied by mobile cell subscription) affect banks’ financial performance, focusing on bank credit and liquid assets, while controlling for inflation and exchange rate variables. It also examines the interaction between digitalization and monetary policy variables on bank performance. Employing an interactive multiple regression model, the study analyzes time series data from 1996 to 2022 sourced from the World Bank. Findings indicate that while stringent monetary policies can constrain bank performance by tightening credit and reducing liquidity, digitalization provides an opportunity for banks to counteract these effects through enhanced efficiency. However, the successful integration of digital technologies is contingent upon adequate investment, regulatory support, and strategic alignment with the banks’ core objectives. The study concludes that Nigerian banks must adeptly manage monetary policy fluctuations and leverage digitalization to sustain and enhance performance. These insights could guide policy formulation and strategic decision-making within the banking industry.

Assessment of a hybrid solar water heating system: environmental impact and economic viability

ABSTRACT Conventional methods of space heating are not only expensive but also environmentally harmful, as they emit greenhouse gases that contribute to global warming. To tackle this issue, a hybrid solar water heating system assisted by a solar evacuated tube collector has been developed at the Madhav Institute of Technology and Science in Gwalior, India. Experiments conducted from November to February 2022–23 (winter season) revealed promising results. Throughout the winter season, the system achieved a daily average effective solar heat collection of 2.85 kWh, with a daily average collector efficiency of 45.5%. The average coefficient of performance (COP) of the solar water heat exchanger was 3.5. Additionally, the system demonstrated an energy payback time of 1.2 years, shorter than that of conventional systems. Over its lifetime, the developed winter heating system is estimated to mitigate 127.9 tonnes of CO2 emissions, earning a carbon credit of $1408. Economic analysis further revealed a favorable benefit-to-cost ratio for the hybrid system, ranging from 3.13 to 3.36, with a payback period varying from 5.03 to 4.47 years for an inflation rate of 6–13%. These findings affirm the feasibility and efficacy of a solar-powered hybrid active winter heating system.

Assessing the Impact of Inflation and Exchange Rate on Nigerian Gross Domestic Product (1981-2022)

This study evaluated the impact of inflation and exchange rate on the Nigerian Gross Domestic Product (GDP) from 1981 to 2022. The data for this study were obtained from Central Bank of Nigeria Statistical Bulletin. Multiple Linear Regression model was adopted for the study to determine the relationship between the GDP, the inflation and exchange rates and the result showed that there is a significant relationship with the p-value (0.005). The result also showed with Ordinary Least Square (OLS) method that inflation rate has a negative impact on the Nigerian GDP while exchange rate is significant with (p-value <0,005) over the years of study. The value of the coefficient of variation R2 for this research is 92.2% indicating that inflation and exchange rate account for about 92% of the variation in the GDP over the years of study. It was observed there was an increase in exchange rate and price level is also detrimental to the economic growth, this means it contributes to the growth of Nigerian GDP over the period of study.

Persistence in the Unemployment and Inflation Relationship. Evidence from 38 OECD Countries

AbstractThis paper focuses on the analysis of persistence in the unemployment and inflation rates in a group of 38 OECD countries as well as on the relationship between the two variables. For this purpose, fractional integration is used. The results indicate that the two individual variables are highly persistent, especially the unemployment rate, and evidence of mean reversion is only found in the cases of Colombia and Costa Rica for unemployment and in Norway for inflation. Conducting the analysis on the difference between the two variables, the order of integration is significantly smaller in a number of cases, and reversion to the mean takes place in the cases of Austria, Switzerland, Costa Rica, Israel, and Turkey. Policy recommendations derived from the results are presented in the concluding section of the article.

IMPACT OF FED RATE ON US DOLLAR - INDIAN RUPEE EXCHANGE RATE

Through this study, we attempt to understand the dynamics of Indian Rupee fluctuations against US Dollar that have been caused by the fluctuations in the Fed Rate. We tried to understand how the Fed Rate influence the Indian rupee - US Dollar exchange rate movements. After research work done via secondary method, we have observed that factors like differential interest rate, differential inflation rate, differential money supply in both the markets, differential output growth rate of both the countries, among others, are important factors which impact the fluctuation in the fed rate that accounts for approximately 91% variance of the Dollar-Rupee exchange rates and explain the exchange rate dynamics to a large extent. A few factors that were earlier considered to be important are not as significant as expected.

Determinants of stock prices in telecommunication industry: An application of fundamental analysis

The present study attempted to assess the impact of fundamental ratios on the share prices of selected telecommunication companies in India. India has dramatically expanded over the past ten years to become the second-biggest telecoms market worldwide, with 1.17 billion users. The Indian telecom industry has proliferated thanks in part to the government of India’s liberal and reformist policies and strong customer demand. It has become a lucrative investment sector for investors due to its recent and prospective growth. Data on 13 telecom firms indexed in the S&P BSE telecommunication index from 2013 to 2022 were taken from companies’ annual reports, the BSE website (Bombay Stock Exchange), and other secondary sources. Six firm-specific fundamental factors viz. Debt to Equity ratio (D/E), Current ratio (CR), Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to earnings ratio (P/E), Return on equity (ROE), and three country-specific fundamental factors viz. Gross Domestic Product, Inflation rate, and S&P BSE Sensex return were considered. Fixed effect panel regression through Generalized Least Square (GLS) model was performed to find inferences. Debt Equity ratio and Inflation rate were found to impact share price negatively. Conversely, the Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to Earnings ratio (P/E), and Return on Equity (ROE) positively impacted selected companies’ share prices. The study results will benefit individual & institutional investors in formulating their investment and portfolio diversification strategies for gaining a high effective rate of return on their investments.

Optimal sizing and economic assessment of grid connected active distribution network for reliable rural electrification in India

Majority of rural areas in India have already been electrified, yet the disparity between demand and supply is considerably higher and broadened due to which nation’s rapid financial growth as well as rising standards of living in both the urban as well as rural areas. Hence, the utilisation of renewable resources is rising steadily for the mitigation of such energy crisis. It has become necessity to use a hybrid sustainable energy system by exploiting the strengths of each source in combination with one another to minimise the dependence on the congested power grid. For the efficient use of readily available renewable energy and sustainable rural electrification, this study proposes an effective Active Distribution Network (ADN). A comprehensive techno-economic analysis has been performed on the design of an ADN system that includes the exploitation of solar and biomass energy as sources of power for sustainable rural electrification. In the proposed work, performance assessment elements such as output responses, component costs, feasibility and sensitivity of the project, emissions, inflation rate, and changing the pricing of integrant have been taken into consideration and analysed. Results shows the improvement in rural electrical system while lowering system energy costs along with consideration of environmental impact.

Liquidity Crunches in the Banking Industry of Nepal

Liquidity crunches in the Nepalese banking sector have been a critical issue for the last few years. This research aims to examine the causes, consequences, and improvement of liquidity crunches in the context of the Nepalese banking industry. This study is based on primary sources with explanatory and descriptive research design. The study population is all the bankers and experts involved in the banking sector - commercial banks, development banks, and regulatory authorities of Pokhara Metropolitan City, Kaski, Nepal. The five-point Likert scale questionnaires were developed to collect the data from the 213 banking professionals based on the non-probability sampling method. This study found a significant impact of government capital expenditure, bank lending policy, and monetary policy on liquidity crunches in the banking industry. The liquidity crunch hampers the growth of business and industry, and discourages entrepreneurs because they are not getting loanable funds as and when required. It creates instability in the financial system, deteriorates the investment environment, generates high inflation and unemployment rates , and affects economic growth rate in the country. The government should increase capital expenditure capacity. Bank lending policy should be directed towards a productive investment. Appropriate monetary policy should be designed to address the liquidity crunch problem in the banking sector. For this, the government and regulatory authority may promote an inclusive and sound financial system in the nation.

Symmetric and Asymmetric Association Between Foreign Direct Investments and Macroeconomic Variables: An Ardl Approach

Objectives: The main objective of the study is to investigating the dynamic relationship between FDI and different Macro Economic Variables (MEVs) using the ARDL procedure, providing a more comprehensive understanding of the association between FDI and MEVs and to evaluate their relative importance for FDI. Methods: This study utilizes annual data from 1991 to 2021 from the World Bank (2021) and the Reserve Bank of India (2021). Data on GDP, Export, Inflation and interest rate, and FDI are collected from the World Bank. Autoregressive Distributive lag Model procedure has been used for the study in order to establish relationship between Macro economic variables and FDI. Results: Our methodological approach using ARDL model and finds: (a) a positive correlation between exports and FDI, (b) a negative impact of inflation and exchange rates on FDI in the long run. Non-linear ARDL analysis reveals the asymmetric impact of inflation and interest rate on FDI, which includes the effect of positive and negative shock of interest rate and inflation on FDI. d) 1% increase in inflation reduces FDI by 0.4% and if Inflation is reduced by 1%, FDI is increased by 0.2%. At the same time, the non-linear estimation of interest rates concludes that there is an asymmetric and significant association between interest rates and FDI. e) If Interest rate has increased by 1% FDI is decreased by 0.9% and if interest rate has reduced by 1% FDI has deceased by 1.63%. f) The causality analysis reveals that exports, GDP, and exchange rates are the significant economic variables that affect FDI. Conclusion: The study's findings have practical implications for policymakers and investors looking to attract more FDI in India. The results indicate that exports play a critical role in attracting FDI and that the government should focus on improving export performance to increase FDI inflows. Additionally, the study highlights the importance of controlling inflation and exchange rates to attract more foreign investment. The finding that interest rates have an asymmetric relationship with FDI suggests that policymakers should be cautious when implementing monetary policies that may impact interest rates. Overall, the study provides valuable insights for policymakers and investors looking to attract more FDI in India and highlights the importance of considering the country's macroeconomic conditions when making investment decisions.

Predicting Indian GDP with Machine Learning: A Comparison of Regression Models

In recent years, the application of machine learning algorithms in economic forecasting has gained significant traction. This study focuses on predicting the Gross Domestic Product (GDP) of India by harnessing advanced machine learning techniques. We assembled a comprehensive dataset incorporating time series analysis and inflation rates from diverse sources. Our investigation involved a comparative analysis employing both linear and polynomial regression methods to discern the most accurate predictive model. Our findings underscore the superiority of the polynomial regression model, which excelled in capturing non-linear relationships between independent variables and GDP. Specifically, the polynomial regression model achieved an impressive prediction accuracy rate of surpassing the accuracy achieved by the linear regression model. This study underscores the critical role of advanced machine learning algorithms in economic forecasting. By emphasizing the significance of high-quality datasets and the application of techniques like polynomial regression, we illustrate how these factors can substantially enhance the precision of economic forecasts. These insights hold substantial implications for policy makers and businesses alike, aiding informed decision-making and effective economic policy development. This study serves as a valuable reference for future research, highlighting the importance of advanced machine learning methods and robust data sources in economic forecasting.

Time-frequency connectedness between electricity prices in Romania and its determinants in the competitive markets

PurposeIn this paper, we aim to provide an extensive analysis to understand how various factors influence electricity prices in competitive markets, focusing on the day-ahead electricity market in Romania.Design/methodology/approachOur study period began in January 2019, before the COVID-19 pandemic, and continued for several months after the onset of the war in Ukraine. During this time, we also consider other challenges like reduced market competitiveness, droughts and water scarcity. Our initial dataset comprises diverse variables: prices of essential energy sources (like gas and oil), Danube River water levels (indicating hydrological conditions), economic indicators (such as inflation and interest rates), total energy consumption and production in Romania and a breakdown of energy generation by source (coal, gas, hydro, oil, nuclear and renewable energy sources) from various data sources. Additionally, we included carbon certificate prices and data on electricity import, export and other related variables. This dataset was collected via application programming interface (API) and web scraping, and then synchronized by date and hour.FindingsWe discover that the competitiveness significantly affected electricity prices in Romania. Furthermore, our study of electricity price trends and their determinants revealed indicators of economic health in 2019 and 2020. However, from 2021 onwards, signs of a potential economic crisis began to emerge, characterized by changes in the normal relationships between prices and quantities, among other factors. Thus, our analysis suggests that electricity prices could serve as a predictive index for economic crises. Overall, the Granger causality findings from 2019 to 2022 offer valuable insights into the factors driving energy market dynamics in Romania, highlighting the importance of economic policies, fuel costs and environmental regulations in shaping these dynamics.Originality/valueWe combine principal component analysis (PCA) to reduce the dataset’s dimensionality. Following this, we use continuous wavelet transform (CWT) to explore frequency-domain relationships between electricity price and quantity in the day-ahead market (DAM) and the components derived from PCA. Our research also delves into the competitiveness level in the DAM from January 2019 to August 2022, analyzing the Herfindahl-Hirschman index (HHI).

The Influence of Macroeconomic Variables on Asean- 5 Countries' Foreign Exchange Reserves Long-Term Relationship and Causality (Empirical Data Year 2014 to 2021)

The country's foreign exchange reserves are an important factor in supporting the economic development process in ASEAN-5 countries. The country's foreign exchange reserves are greatly influenced by macroeconomics so macroeconomic changes will have a large and rapid impact on foreign exchange reserves. So this research aims to determine the influence of macroeconomics, namely the rate of inflation, exchange rate, export value, and economic growth on the foreign exchange reserves of ASEAN-5 countries. The data processing was carried out using the multiple panel data regression method, empirical data from 2014 to 2021. The results of the data processing that has been carried out show that the model test, together with the inflation rate, exchange rate, export value, and economic growth, has an effect of 94.9867 percent. to the foreign exchange reserves of ASEAN-5 countries. Meanwhile, partially the export value and economic growth variables have a significant effect on ASEAN countries' foreign exchange reserves and are positively proportional, but the inflation rate and exchange rate have no effect on ASEAN countries' foreign exchange reserves and are negatively proportional. Apart from that, the role of the government is also very influential in maintaining the country's foreign exchange reserves because macroeconomics is determined by government policies.

Geo-Economic Changes in the Development of the Financial and Credit Policy of the Agro-Food Industry of Ukraine

The article examines effective measures for the development of the financial and credit policy of the agro-food industry of Ukraine in the geo-economic space. Proved that financialization in geo-economics has a global vector of development, which transforms the models of the general balance of financial and credit flows. The geo-financial ap-proach is presented. A detailed analysis of Ukraine's foreign trade with the EU was carried out, and the specific structure of exports of agro-food products was determined. The geographical structure of the geo-financial system of Ukraine. The influence of currency risks on the export of grain crops on average per subject of the agro-food industry of Ukraine was calculated. The dynamic fluctuations of the inflation rate. The structure of the sources of the formation of the financial and credit system of the agro-food industry of Ukraine by global financial institutions during the period of martial law is given. Received: 20 February 2024 / Accepted: 26 April 2024 / Published: 5 May 2024

Evaluating the Impact of Inflation and Exchange Rates on the Net Active Value (NAV) of Conventional Mutual Funds in Indonesia

The growing development in the financial industry and the current high inflation rate are a great worry for investment prospects, especially mutual funds. Conventional mutual funds in Indonesia have experienced significant growth in the capital market. In the last 10 years, the number of domestic mutual funds has continued to increase. One measure of investment performance in mutual funds is proxied by the Net Asset Value (NAV) of mutual funds. Therefore, the objective of this study is to evaluate the influence of macroeconomics variables on the NAV of conventional mutual funds in Indonesia. In this study, using commercial bank data in Indonesia, we estimate an empirical model of the effect of inflation and exchange rates on the NAV of conventional mutual funds in Indonesia during the period 2012–2022. We employ a time series model using the Ordinary Least Square (OLS). The main findings show that while inflation has no effect on the NAV of conventional mutual funds, the exchange rate has a significant effect on it because there are many instruments in conventional mutual funds that have invested abroad due to changes in exchange rates that appear with dominant results that do not affect the growth of the NAV of conventional mutual funds. Keywords: macroeconomics, net active value (NAV), mutual funds

IMPACT OF CREDIT, INTEREST RATE AND INFLATION ON SMALL AND MEDIUM ENTERPRISES PRODUCTIVITY IN NIGERIA

This study sought to evaluate the impact of credit, interest rate and inflation on Small and Medium Enterprises Productivity in Nigeria, using annual time series data from 1986-2023. The data for the study was sourced from the World Development Indicator (WDI) and the Central Bank of Nigeria (CBN) statistical bulletin. The data collected were gross domestic product (GDP) which is the dependent variable while commercial bank total credit to private sector (CPS), small and medium enterprises contribution to GDP (SMEC), inflation rate (INFL) and interest rate (INT) are the independent variables. Descriptive, inferential statistics and Error Correction Model (ECM) were used to test the long run relationship of the variables. The results of the regression show that credit to private sector and small and medium enterprises contribution to gross domestic product is positive and significant to economic growth. The results further revealed that inflation rate and interest rate have a negative and insignificant effect on gross domestic product. The study recommends that government should put more efforts to curb inflation to give more confident to investors and should implement measures (low interest rates) that would broaden the borrowing base to improve financial capacity of SMEs, thus lead to an increase in the contribution of SMEs to nations GDP. KEYWORD: SME, Interest rate, Inflation, GDP.

Abstract PO5-05-10: Analysis of Trends in Funding of Metastatic Breast Cancer Research

Abstract Introduction To inform funding strategies for research in metastatic breast cancer (MBC), knowledge of the current research landscape and identification of potential gap areas requiring additional research are essential. In 2014, the Metastatic Breast Cancer Alliance (MBCA) published an analysis that showed that between 2000 and 2013, only 7% of all funds for breast cancer research were devoted to metastasis. As more people are living with MBC, addressing research priorities for those living with the disease is important, as is understanding gaps in the current funding landscape of MBC research to appropriately target investment. Methods A collaborative effort between funders and patients was undertaken to analyze breast cancer projects funded between 2014 and 2020 from the International Cancer Research Partnership database, the Health Resource Alliance database, and MBCA members, representing grants from 83 non-profit organizations worldwide. Project titles, abstracts, and classifications of these grants were extracted from these databases. Next, to identify research projects in the databases that are related to metastasis, a classification tool that uses a machine learning algorithm was built, trained on manually coded grants from the 2000-2013 analysis, and validated by expert coders. Projects were then coded according to a pre-established metastasis classification policy to categories such as type of research (e.g., treatment), genes or proteins studied, site of metastasis, breast cancer subtype, and patient priority questions. In terms of the latter, MBCA members living with MBC were surveyed about research priorities. Member advocates ranked survey questions according to highest patient priority, and these were converted to language that could be queried with the tool. Results Investment in MBC research nearly doubled from 2014 to 2020. Research into understanding and overcoming treatment resistance, which was the highest patient priority question, increased from 15% in 2014 to 26% of the MBC portfolio in 2020; this was a statistically significant increase above the rate of inflation. In terms of treatment resistance according to subtype, the highest number of projects focused on triple-negative MBC (>300). By contrast, < 20 projects were focused on overcoming treatment resistance in metastatic invasive lobular breast cancer. Of the six categories evaluated (e.g. biology and detection/diagnosis/prognosis), the largest increase in investment was for treatments. Discussion The coding tool allows for ongoing complex queries such as identification of funded research relevant to areas identified as important by MBC advocates (Table) and provides a funders’ ‘dashboard’ to identify gap areas in need of further research funding. This collaborative effort between funders and patient advocates, and the resulting current and future analyses, can be used to focus advocacy efforts to drive research funding of priorities and understudied areas of MBC. Despite the increase in funding, the investment in metastatic research–the primary cause of death from breast cancer–remains insufficient. Table. Research Priorities of MBC Patient Advocates Citation Format: Margaret Flowers, Teri Pollastro, Kari Wojtanik, Katherine McKenzie, Kimberly Badovinac, Medha Deoras-Sutliff, Lynne Davies. Analysis of Trends in Funding of Metastatic Breast Cancer Research [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-05-10.

GRU-RNN Model to Analyze and Predict the Inflation by Consumer Price Index

The general population need data on the expected rate of inflation for educational expenses to plan for and manage family budgets. When formulating educational policy, this data is also useful for the government. Chennai serves as one of Indonesia's educational hubs, yet there is a lack of publicly accessible data on the city's inflation rate for education expenses. Furthermore, there is a lack of prior studies on forecasting that specifically used the Education Expenditure Group's Consumer Price Index (CPI) information to determine inflation rates in education prices utilizing the Deep Learning approach. The goal of this study is to utilize the Deep Learning Method to create a model that can predict how much tuition will rise in Chennai. The Education Expenditure Group in Chennai relied on Consumer Price Index (CPI) information for its study. An improvement in the Long and Short-Term Memory (LSTM) and Recurrent Neural Network (RNN), approach is used for predicting purposes. A method with four hidden nodes and a single hidden layer produced the best results, with RMSE=8.38 and MAPE=2.8766%.