Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6, 1631-1650 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 18 April 2025; Revised: 19 May 2025; Accepted: 22 May 2025; Published: 19 June 2025 * Correspondence: rashasaab_lb@hotmail.com Inflation determinants and its effect on economic growth: The case of Lebanon Rasha Saab1*, Hanadi Taher2 1,2Beirut Arab University, Lebanon; rashasaab_lb@hotmail.com (R.S.) h.taher@bau.edu.lb (H.T.) Abstract: This study examines the factors influencing inflation and how it affects Lebanon’s economic growth using annual data from 1990 to 2022 through the ARDL technique. The current study employs the ARDL model under the Pesaran, et al. [1] testing approach, the Augmented Dickey-Fuller (ADF) test, and additional diagnostic tests to ensure no serial correlation or heteroscedasticity. It also applies CUSUM, CUSUM Square, and Ramsey tests to assess the impact of inflation on Lebanon’s economic growth. Under the ARDL assumptions, the study demonstrates that household consumption and government debt have a significant, long-term, positive influence on inflation but do not influence inflation over the short term. Other findings show that the rate of inflation has an adverse effect on both long- and short-term economic growth. Researching inflation and its impact on economic growth is vital to understanding how price levels affect economic stability. Inflation shapes policies, influences investments, affects purchasing power, and determines the long-term sustainability of growth. Accordingly, stable inflation fosters sustained development. The findings guide policymakers in managing consumption and debt to control inflation, while helping central banks curb inflation to support sustainable economic growth in Lebanon. Keywords: ARDL, Economic growth, Inflation. 1. Introduction Uncertainty and fear are prevalent features when it comes to economic issues like inflation. Inflation as broadly stated, is the continuous rise in the prices of services and products within a specific economy. Inflation reduces the purchasing power of money. Thus, maintaining price stability is one of any economy’s top economic goals [2]. Where the source of inflation is the core of the dispute, economists hold different views on the factors that determine inflation. Smith (1776) as cited in Bordo and Rockoff [3] for instance came to a conclusion that inflation is only triggered by increases in money supply. So, as long as the government controls the money supply, there won't be an inflationary environment. According to Keynes, under full employment, inflation is caused when aggregate demand exceeds aggregate supply (Keynes, 1936 cited in Meltzer [4]). Friedman (1963) as cited in Salami and Kelikume [5] argues that an excess in the quantity of money above the supply of output is termed as inflation. In fact, debates differ due to different views regarding the best way to combat inflation with the fact that there are variations taking place between advanced and emerging nations. In developing nations, who are mainly, socially polarized, less democratic, have low economic freedom indices, have a history of high political instability, and have high levels of domestic debt to GDP ratio with limited access to finance their internal as well as external debt; they experience as agreed by the majority of economists higher levels of seigniorage and inflation [6]. https://orcid.org/0009-0001-3299-7963 https://orcid.org/0000-0001-8052-1807 1632 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate Regarding economic growth and inflation, there is ongoing discussion on the association between the two. Still in both developed and emerging nations, the fundamental objective of any macroeconomic strategy is to maintain a low one-digit rate of inflation while promoting rapid economic growth [7]. In general, there are four major hypotheses explaining how output and growth are influenced by inflation. As noted by Akinsola and Odhiambo [8] contends that growth is somewhat influenced by inflation, while Tobin [9] argues that inflation promotes long-term growth and Stockman [10] argues that inflation negatively affects growth. Inflation as per Khan and Ssnhadji [11] has an adverse impact on long-term growth, but only if it is over a certain threshold. Still, most central banks and policymakers agree that low inflation or price stability would provide conditions for higher economic growth and that inflation is an obstacle to it. This study looks at the long-and short-term factors influencing inflation in Lebanon and how it impacts economic growth using annual data for the time span 1990 to 2022. The remaining sections of the paper are as follows: Section 2 summarizes a few research that is more relevant to the field of work along with the hypotheses. In Section 3, the methodology is discussed along with the econometric models. Section 4 presents the discussion of the findings and outcomes. Conclusion is provided in the last section. 2. Literature Review Numerous factors have been used in literature to explain inflation and are believed to be its corresponding determinants. Mirza and Rashidi [12] provided evidence of the causal linkage between lending interest rate and inflation. The association between deposit interest rate and inflation was noted by Biçen [13]. Al-Mutairi, et al. [14] looked into how taxes, exchange rate, interest rates, and money supply are related to inflation. Munir [15] examined how inflation is affected by real effective exchange rate. George-Anokwuru and Ekpenyong [16] found out how government spending influenced the rate of inflation. Rachman [17] studied the correlation between governmental revenues and inflation rate. Kwon, et al. [18] assessed the correlation between public debt and the rate of inflation. Numerous research found that inflation and interest rates are positively related [19, 20]. conversely, Hashim, et al. [21] found an adverse correlation between the two variables. Money supply according to Armesh, et al. [22] and Iya and Aminu [23] influences inflation positively over the long- term. Conversely, Jawo, et al. [24] argue that inflation is adversely influenced by money supply over the short run term. This influence turns positive over the long term whereas Abasimi, et al. [25] found that money supply has no influence on short- and long-term inflation. Exchange rate is one of the key elements identified by many researchers as affecting inflation dynamics. In real terms, Asad, et al. [26] came to a conclusion that real effective exchange rate and inflation are positively correlated. However, Munir [15] found that real effective exchange rate has an adverse and significant long-term impact on inflation. Results differ about the correlation between governmental spending and the rate of inflation. Mehrara and Sujoudi [27] noted that inflation is not impacted by governmental spending neither over the long nor over the short run term. This contrasts the findings of George-Anokwuru and Ekpenyong [16] who found that even though there is a short term, positive, but insignificant, correlation between government spending and the rate of inflation, an adverse relation is present over the long term. The linkage between government revenues and the rate of inflation has not been heavily studied. Maskie and Hoetoro [28] concluded that government revenue boosts the level of inflation by around 1.17%. The correlation between governmental debt and inflation has been well studied in literature. Kwon, et al. [18] suggested that growing public debt generally leads to higher inflation in nations with significant debt levels. However, Harmon [29] found a positive weak correlation between state debt and inflation. More precisely, Sharaf and Shahen [30] argued that external debt has negligible long-term influence on inflation. 1633 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate According to Bonsu and Muzindutsi [31] household consumption is thought to be an important factor driving aggregate demand. One addition made by this study is the discussion of the impact of consumer spending on inflation which has not been heavily studied in literature. Critiques of research on the factors that influence inflation frequently highlight a number of important issues such as methodological issues, the intricacy of the underlying causes of inflation. A prevalent issue is the propensity to overemphasize monetary considerations, which could lead to policy proposals that narrowly concentrate on changing monetary policy either by tightening or expanding it. This may limit the effectiveness of policy responses by ignoring significant non-monetary factors that also contribute to inflation. A more thorough understanding of inflation dynamics requires a more balanced approach that considers both non-monetary and monetary factors [32, 33]. Two hypotheses are developed based on the literature mentioned above: H1: Public debt negatively influences inflation. H2: household consumption positively influences inflation. GDP is the total cumulative production of an economy. It is the aggregate sum of the monetary values of all services and products that an economy generates over a specific time. An increase in production would result in higher salaries, higher spending but lower unemployment all of which could drive up inflation [34]. Gillman, et al. [35] highlighted the inflation-economic growth relationship for 18 APEC and 29 OECD member nations. Inflation-growth interactions were found to be negative. Conversely, upon applying the endogenous threshold auto regressive model, Munir and Mansur [36] reached to a conclusion that as inflation rate is below the level of 3.89%, economic growth is positively influenced by inflation. Beyond this, inflation has an adverse influence. Vinayagathasan [37] used the concept of dynamic threshold analysis to analyze 32 Asian countries, and a threshold of 5.43% was put under scope. Growth was negatively impacted by rates above this threshold and was unaffected by rates below it. Odhiambo [38] emphasized both theoretical and empirical evidence related to inflation and economic growth in emerging and developed nations. According to their analysis, inflation’s impact on economic growth fluctuates over time and between countries. Results are influenced by the contry specific factors, data set employed and the technique used. Kırşanlı [39] upon investigating 38 OECD countries from 1972 to 2021 found that inflation adversely affects economic growth, with a 1% increase in inflation reducing economic growth by 0.03% to 0.15% depending on the model used. Lubeniq, et al. [40] examined the non-linear relationship between inflation and economicgrowth in 20 developing European countries from 1995 to 2022, finding that a 1% increase in inflation adversely impacts economic growth by approximately 0.017%. Hussain [41] in turn added that inflation has a negative and significant impact on Pakistan’s economic growth in both the short and long run using data from 1973 to 2022. Overall, empirical results reported in litrature may generally be divided into four categories or groups: Cameron, et al. [42] asserts that there is no statisticaly significant impact taking place between inflation and economic growth. According to Benhabib and Spiegel [43] inflation promotes economic growth. Referring to Valdovinos [44] inflation has adverse effects. To add, at some point or threshold, inflation begins to affect economic growth [45]. Inlight of the aforementioned hypothesis three is stated asfollows: H3: Inflation negatively influences economic growth. In fact, research on the inflation-economic growth relationship frequently encounters several challenges that may result in inaccurate findings. For instance, results may be impacted by the choice of inflation and economic growth measures [46]. Furthermore, many studies do not distinguish between cost-push and demand-pull inflation, where the impact of inflation can have quite different effects on economic growth depending on its source [47]. 1634 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate The inflation-economic growth relationship can vary depending on the time frame analyzed. Short term effects may differ from long-term effects. Many studies overlook this distinction [11]. Inflation-growth dynamics may differ significantly between advanced economies and developing countries, or between countries with different institutional settings and policy frameworks [48]. There is no consensus on the theoretical framework that better explains the inflation-economic growth relationship. Fischer [49] examines different theoretical perspectives on inflation and growth, noting the conflicting views on whether moderate inflation fosters or hampers growth. These critiques highlight the complexity of studying the inflation-growth relationship and underscore the need for more sophisticated methods, better data and a nuanced understanding of the underlying mechanisms at play. 3. Method The autoregressive distributed lag (ARDL) testing approach will be employed in this study to put under scope the factors that determine inflation and how it affects economic growth in Lebanon under two separate models. The time frame chosen depends on the data’s availability. Time series analysis creates mathematical models that offer plausible interpretations for the sample data [50]. Annual data from 1990 to 2022 is sourced from the world bank and IMF. According to, Shin, et al. [51]; Pesaran, et al. [1] and Pesaran and Shin [52] ARDL is built on the notion that all variables ought to be integrated at first difference or at level. They might be mutually integrated but never integrated at I(2).This is the main benefit that strengthens the ARDL model and makes it suitable for the current study. Also, a wide range of lag structures can be addressed by ARDL. In contrast to other cointegrating techniques, ARDL is also appropriate for small sample sizes. Based on Bashir [34]; Mirza and Rashidi [12]; Kia and Sotomayor [53]; Dilanchiev and Taktakishvili [54] and Munir [15] who tested different variables that may have an impact on inflation the model employed is: 𝐼𝑁𝐹𝑡 = 𝛽0+𝛽1𝐿𝐸𝑁𝐷𝑡 + 𝛽2𝐷𝐸𝑃𝑡 + 𝛽3𝑀𝑡 + 𝛽4𝐸𝑋𝐶𝐻𝑡 + 𝛽5𝐸𝑋𝑡 + 𝛽6𝑅𝐸𝑉𝑡 + 𝛽7𝐷𝐸𝐵𝑇𝑡 + 𝛽8𝐶𝑂𝑁𝑆𝑡 + 𝜀𝑡 (1). Personal consumption expenditure is used in place of the consumer price index based on McCully, et al. [55]. Based on Fatima, et al. [56]; Yamin, et al. [57]; Okisai, et al. [58]; Shrestha and Kautish [59]; Hicham [60]; Yuliastanti, et al. [61]; Utile, et al. [62]; Dudzevičiūtė, et al. [63] and Pavlic, et al. [64] another model is bult. It has the following specification: EGt=𝛽0 + 𝛽1𝐿𝐸𝑁𝐷𝑡+𝛽2𝐷𝐸𝑃𝑡 + 𝛽3𝑀𝑡 𝛽4𝐸𝑋𝐶𝐻𝑡 + 𝛽5𝐸𝑋𝑡 𝛽6𝑅𝐸𝑉𝑡+𝛽7𝐷𝐸𝐵𝑇𝑡+𝛽8𝐶𝑂𝑁𝑆𝑡 + 𝛽9𝐼𝑁𝐹𝑡 + 𝜀𝑡 (2) The dependent variable of equation (1) is INF which stands for inflation as measured by personal consumption expenditure (PCE). Personal consumption expenditure is defined as nominal consumption over real consumption in constant 2015 USD ×100. The dependent variable in equation (2) is EG which stands for economic growth. It is determined as the percentage change in real GDP which is in constant 2015 USD. 𝛽0 is the intercept in both models. 𝛽1….𝛽9 are the coefficients of the models. The following are the independent variables: (lend) which is the real lending interest rate in percentage, (DEP) which is the real deposit interest rate in percentage, (M) which represents the broad money in constant 2015 USD, (EXCH) which is the real effective exchange rate, (EX) which is the total government expenditure in constant 2015 USD, (REV) which is the government revenues in constant 2015 USD, (DEBT) which is the total debt in constant 2015 USD, and (CONS) which is the household consumption expenditure in constant 2015 USD, 𝜀𝑡 is the error term. Variables excluding interest rates are expressed in logarithmic form. The ARDL technique will be used in this investigation. The need to look at the ADF unit root test is the first step (Dickey & Fuller, 1981 cited in Chang and Park [65]). Verifying the variables’ long- term cointegration is the second step. 𝐻0which denotes no long-run cointegration, cannot be rejected if the F- statistic is lower than the critical values. The hypothesis is only rejected when the computed F- 1635 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate statistic exceeds both the lower and upper critical F-values. No conclusion can be made if the F-statistic falls between the two critical values [1, 52]. The third step entails conducting stability and diagnostic tests to assess the models’ goodness of fit. The diagnostic analysis checks for heteroscedasticity, serial correlation, and normality distribution of the residuals. As suggested by Brown et al. (1975 cited in Dritsaki and Stamatiou [66]), the test of stability is conducted using CUSUM and CUSUM square tests. 4. Results Testing the stationarity of the ARDL model is the first step in the analytical process. According to Yule [67] a series is non stationary if having a unit root. The variables’ integration order in the model can be established with the use of ADF. ADF is a popular and efficient unit root test for determining whether the model series is stationary (Dickey & Fuller, 1981 cited in Chang and Park [65]). At the 5% significance level, Table 1 illustrates that, except for DEP and CONS, which are integrated at level I(0, all other variables are integrated at first difference I(1). Table 1. Unit root tests (ADF) on the individual series. Variables Series P-value Series in first difference P-value Test statistic Dickey-Fuller critical value (5%) Test statistic Dickey- Fuller critical value (5%) INF -1.8973 -2.960411 0.3292 -3.0163 -2.963972 0.0447 LEND -2.6016 -2.957110 0.1031 -8.446 -2.963972 0.0000 DEP -3.6561 -2.986225 0.0117 - - - M -2.5323 -2.957110 0.1176 -4.3183 -2.960411 0.0019 EXCH 0.8916 -2.998064 0.9977 -2.413 -2.963972 0.0017 EX -2.2193 -2.963972 0.2039 -4.4384 -2.963972 0.0015 REV -0.7587 -2.960411 0.8167 -5.2814 -2.960411 0.0001 DEBT -2.7706 -2.963972 0.0745 -7.5117 -2.960411 0.0000 CONS -4.9401 -2.957110 0.0003 - - - EC -1.9985 -2.963972 0.2859 -5.2144 -2.960411 0.0002 The ARDL model responds to the number of lag order. The model with the lowest Schwartz information criterion (SBIC), and Akaike Information Criterion (AIC) is determined. This is identified by Stock and Watson [68]. Table 2. Maximum number of lags Inflation Model. Lag AIC SBIC HQIC 0 5.270660 5.686979 5.406370 1 -16.65112* -8.741057* -14.07263* 2 -8.073187 -3.909998 -6.716091 Note: The optimal lag is denoted by * . Table 3. Maximum number of lags Economic Growth Model Lag AIC SBIC HQIC 0 0.765087 1.227664 0.915876 1 -26.83632* -17.12222* -23.66977* 2 -14.43535 -9.347005 -12.77667 Note: The optimal lag is denoted by * The maximum lag when using Hannan-Quinn Information Criterion (HQIC), Schwarz information criterion (SBIC), and Akaike Information Criterion (AIC) is displayed in Table 2. 1 is the optimal lag. 1636 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate Among other lags, it shows the lowest value (-16.65112 for AIC; -8.741057 for SBIC; -14.07263 for HQIC). Similarly, the optimal lag is also 1 in table 3. Among other lags, it shows the minimum value (- 26.83632 for AIC; -17.12222 for SBIC; -23.66977 for HQIC). The initial step in model estimating is to perform the ARDL regression at the optimal distributed lags based on Akaike and schwarz criterion [68]. Examining the long and short- term correlation among the variables is the second step. Table 4. ARDL regression Inflation Model. ARDL(1, 0, 0, 1, 0, 1, 0, 1, 0) regression Sample: 1990-2022 Observations 32 R-squared 0.9852 Adjusted R-squared 0.9759 Root Mean Squared Error (RMSE) 0.0397 F-statistic 106.0200 Log Likelihood = 65.36 Prob > F 0.0000 inf Coefficient Standard err. T P > |t| [Cl 95%] inf L1 0.602430 0.150343 4.007031 0.0006 0.307758 0.897102 lend L0 0.003396 0.007149 0.475012 0.6395 -0.01062 0.017408 dep L0 -0.006094 0.007903 -0.771059 0.4489 -0.02158 0.009396 M L0 -0.248520 0.151916 -1.635903 0.1161 -0.54628 0.049235 L1 0.577303 0.211263 2.732632 0.0132 0.163228 0.991378 EXCH L0 0.189604 0.104758 1.809921 0.0840 -0.01572 0.39493 EX L0 0.005102 0.047873 0.106579 0.9161 -0.08873 0.098933 L1 -0.165189 0.046286 -3.568898 0.0020 -0.25591 -0.07447 REV L0 0.394268 0.168314 2.342455 0.0286 0.064373 0.724163 DEBT L0 -0.016293 0.078462 -0.207662 0.8374 -0.17008 0.137493 L1 -0.146754 0.096400 -1.522349 0.1444 -0.3357 0.04219 CONS L0 0.054027 0.109975 0.491267 0.6281 -0.16152 0.269578 Table 4 shows that public debt (DEBT) does not influence inflation rate at and 10% level. This finding is in line with Osei [69]. Household consumption (CONS) has no impact on inflation. Test of significance using p-value is based on Rao [70]. If the observed value of the selected test statistic surpasses the computed value of the test statistics in the 95% or 99% percentile the null hypothesis (𝐻0) is rejected. 1637 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate Table 5. ARDL regression Economic Growth Model. ARDL (1, 0, 0, 1, 1, 1, 1, 0, 0, 0) regression Sample: 1990-2022 Observations 32 R-squared 0.9986 Adjusted R-squared 0.9975 Root Mean Squared Error 0.0147 F-statistic 917.4384 Log Likelihood = 94.71 Prob > F 0.0000 EG Coefficient Standard err. T P > |t| [CI 95%] EG L1 0.274768 0.149575 1.836990 0.0838 -0.040808 0.590344 lend L0 0.000767 0.002533 0.302686 0.7658 -0.004577 0.006110 dep L0 -0.001440 0.002825 -0.509739 0.6168 -0.007401 0.004521 M L0 0.415783 0.124740 3.333187 0.0039 0.152604 0.678963 L1 -0.272844 0.109814 -2.484598 0.0237 -0.504533 -0.041156 EXCH L0 -0.078654 0.054913 -1.432336 0.1702 -0.194510 0.037202 L1 -0.098466 0.059767 -1.647491 0.1178 -0.224563 0.027632 EX L0 0.041177 0.026301 1.565631 0.1359 -0.014312 0.096667 L1 -0.089422 0.025236 -3.543432 0.0025 -0.142665 -0.036179 REV L0 -0.016467 0.067986 -0.242212 0.8115 -0.159904 0.126970 L1 -0.109518 0.044398 -2.466743 0.0246 -0.203190 -0.015847 DEBT L0 0.103989 0.040293 2.580842 0.0194 0.018979 0.188999 CONS L0 0.357248 0.075052 4.759978 0.0002 0.198901 0.515595 INF L0 -0.382326 0.076513 -4.996900 0.0001 -0.543753 -0.220898 In Table 5, while inflation (INF) adversely influences economic growth at 1% level, household consumption (CONS) and public debt (DEBT) positively influences economic growth at 1% and 5% level respectively. Significance test is built on Rao [70]. In Table 6, ADJ to INF has a value of (-0.397570) representing the velocity of adjustment. This number indicates the rate at which the equilibrium distortion takes place. Long run coefficients in the first part of table 6 demonstrates that public debt (DEBT) and household consumption (CONS) influences inflation rate positively at 1% and 5% level respectively. Thus 𝐻1 is rejected while 𝐻2 is accepted. Test of significance using p-values is based on Rao [70]. 1638 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate Table 6. ARDL short and long-run results Inflation Model. ARDL (1, 0, 0, 1, 0, 1, 0, 1, 0) regression Sample: 1990-2022 Observations 32 R-squared 0.6694 Adjusted R-squared 0.6584 Log Likelihood = 55.48 Root Mean Squared Error (RMSE) 0.0397 INF Coefficient Standard err. T P > |t| [CI 95%] ADJ INF L1 -0.397570 0.150343 -2.644414 0.0148 -0.6922 -0.1028 LR LEND 0.006790 0.018203 0.373012 0.7244 -0.0288 0.0424 DEP -0.007942 0.019930 -0.398516 0.7067 -0.047 0.0311 M 3.560058 1.020251 3.489395 0.0175 1.5603 5.5597 EXCH 2.207147 0.428392 5.152170 0.0036 1.3674 3.0467 EX -0.156059 0.136543 -1.142932 0.3048 -0.4236 0.1115 REV 2.411545 0.478384 5.041022 0.0040 1.4739 3.3491 DEBT 3.319138 0.713847 4.649645 0.0056 1.9199 4.7182 CONS 3.998137 1.020576 3.917530 0.0112 1.9978 5.9984 SR LEND D1. 0.003396 0.007149 0.475012 0.6395 -0.01062 0.017408 DEP D1. -0.006094 0.007903 -0.771059 0.4489 -0.02158 0.009396 M D1. -0.248520 0.151916 -1.635903 0.1161 -0.54628 0.049235 EXCH D1. 0.189604 0.104758 1.809921 0.0840 -0.01572 0.39493 EX D1. 0.005102 0.047873 0.106579 0.9161 -0.08873 0.098933 REV D1. 0.394268 0.168314 2.342455 0.0286 0.064373 0.724163 DEBT D1. -0.016293 0.078462 -0.207662 0.8374 -0.17008 0.137493 CONS D1. 0.054027 0.109975 0.491267 0.6281 -0.16152 0.269578 Similarly, in Table 7, ADJ to Economic growth (EG) showed value of (-0.725232) representing the velocity of adjustment and the rate at which the equilibrium distortion occurs. Long run coefficients and short-term coefficients are also displayed in table 7. Inflation (INF) and public debt (DEBT) adversely affects short-term economic growth at 1% and 5% level respectively. In the long and short -run term, economic growth is positively influenced by household consumption (CONS) at a level of significance of 1%. Test of Significance is based on Rao [70]. At 1% level of significance, economic growth is adversely impacted by inflation in the long-run term. Hence, 𝐻3is accepted. 1639 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate Table 7. ARDL long-run and short-run results Economic Growth Model. ARDL (1, 0, 0, 1, 1, 1, 1, 0, 0, 0) regression Sample: 1990-2022 Observations 32 R-squared 0.9821 Adjusted R-squared 0.9786 Log Likelihood = 94.71 Root Mean Squared Error (MSE) 0.0147 EG Coefficient Standard err. T P > |t| [CI 95%] ADJ EG L1 -0.725232 0.149575 -4.848617 0.0002 -1.0184 -0.43207 LR LEND 0.001057 0.003486 0.303263 0.7654 -0.00578 0.00789 DEP -0.001986 0.003911 -0.507826 0.6181 -0.00965 0.00568 M 0.197094 0.077821 2.532646 0.0215 0.044565 0.349623 EXCH -0.244225 0.098112 -2.489247 0.0235 -0.43652 -0.05193 EX -0.066523 0.043762 -1.520097 0.1469 -0.1523 0.019251 REV -0.173717 0.131786 -1.318173 0.2049 -0.43202 0.084584 DEBT -0.143387 0.072688 -1.972649 0.0650 -0.28586 -0.00092 CONS 0.492599 0.065149 7.561086 0.0000 0.364907 0.620291 INF -0.527177 0.102089 -5.163879 0.0001 -0.72727 -0.32708 SR LEND D1. 0.000767 0.002533 0.302686 0.7658 -0.0042 0.005732 DEP D1. -0.001440 0.002825 -0.509739 0.6168 -0.00698 0.004097 M D1. 0.415783 0.124740 3.333187 0.0039 0.171293 0.660273 EXCH D1. -0.078654 0.054913 -1.432336 0.1702 -0.18628 0.028975 EX D1. 0.041177 0.026301 1.565631 0.1359 -0.01037 0.092727 REV D1. -0.016467 0.067986 -0.242212 0.8115 -0.14972 0.116786 DEBT D1. -0.103989 0.040293 -2.580842 0.0194 -0.18296 -0.02501 CONS D1. 0.357248 0.075052 4.759978 0.0002 0.210146 0.50435 INF D1. -0.382326 0.076513 -4.996900 0.0001 -0.53229 -0.23236 To look over the long run relationship among the variables, the ARDL bound test as a co- integration method is utilized. Table 8. Bound test Inflation Model. H0: No long-run relationships exist F 4.9505 Third case t -7.7946 F test 10% 5% 1% I (0) I (1) I (0) I (1) I (0) I (1) F 1.95 3.06 2.22 3.39 2.79 4.1 T -2.57 -4.4 -2.86 -4.72 -3.43 -5.37 1640 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate Table 9. Bound test Economic Growth Model H0: No long-run relationships exist F 27.36073 Third case t -20.45625 F test 10% 5% 1% I (0) I (1) I (0) I (1) I (0) I (1) F 1.88 2.99 2.14 3.3 2.65 3.97 T -2.57 -4.56 -2.86 -4.88 -3.43 -5.54 Based on Table 8 and Table 9 results, the F- statistic is (4.9505) and (27.36073) respectively. At 10%, 5% and 1% level, these values exceed the critical values. Thus, 𝐻0is rejected [71]. Consequently, the variables have long term association. For diagnosing both the inflation and economic growth models, certain econometric tests including normality, heteroscedasticity and serial correlation are essential. Misspecification test i.e., Ramsey RESET test is also applied. Additionally, when evaluating the models’ stability (CUSUM) and CUSUM square tests are represented. Jarque-Bera normality test is passed by both inflation and economic growth models; where p-value in Figure 1 and Figure 2 indicate that 𝐻0 ( 𝑡ℎ𝑒 𝑑𝑖𝑠𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 𝑖𝑠 𝑛𝑜𝑟𝑚𝑎𝐿) is not rejected at 10% level of significance (Jarque-Bera,1980 cited in Thadewald and Büning [72]). 0 2 4 6 8 10 12 -0.10 -0.05 0.00 0.05 0.10 Series: Residuals Sample 1991 2022 Observations 32 Mean 3.47e-16 Median -0.002445 Maximum 0.097090 Minimum -0.101337 Std. Dev. 0.043408 Skewness -0.169069 Kurtosis 3.113923 Jarque-Bera 0.169755 Probability 0.918625 Figure 1. Normality Test Inflation Model. 1641 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate 0 1 2 3 4 5 6 7 -0.03 -0.02 -0.01 0.00 0.01 0.02 Series: Residuals Sample 1991 2022 Observations 32 Mean 2.71e-16 Median -0.000565 Maximum 0.024004 Minimum -0.027224 Std. Dev. 0.012742 Skewness -0.161399 Kurtosis 2.481741 Jarque-Bera 0.497055 Probability 0.779948 Figure 2. Normality Test Economic Growth. Table 10. Serial Correlation Test Inflation Model. Breusch-Godfrey Serial Correlation LM Test: F-statistic 0.365414 Prob. F (2,20) 0.6984 Obs*R-squared 1.128102 Prob. Chi-Square(2) 0.5689 Table 11. Serial Correlation Economic Growth Model. Breusch-Godfrey Serial Correlation LM Test: F-statistic 0.767439 Prob. F(2,15) 0.4816 Obs*R-squared 2.970453 Prob. Chi-Square(2) 0.2265 Table 10 and Table 11 show the absence of autocorrelation where p-value indicates that 𝐻0 ( 𝑡ℎ𝑒 𝑟𝑒𝑠𝑖𝑑𝑢𝑎𝑙𝑠 𝑎𝑟𝑒 𝑛𝑜𝑡 𝑐𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑒𝑑) is not rejected at 10% level of significance (Breusch, 1978; Godfrey, 1978 cited in Uyanto [73]). Table 12. Heteroscedasticity Test Inflation Model. Heteroscedasticity Test: Breusch-Pagan-Godfrey F-statistic 0.678647 Prob. F(28,15) 0.7515 Obs*R-squared 9.60075 Prob. Chi- Square(28) 0.6509 Scaled explained SS 2.857726 Prob. Chi- Square(28) 0.9965 Table 13: Heteroscedasticity Test Economic Growth Model. Heteroscedasticity Test: Breusch-Pagan-Godfrey F-statistic 0.582647 Prob. F(9,36) 0.8437 Obs*R-squared 10.37585 Prob. Chi- Square(9) 0.7342 Scaled explained SS 2.16952 Prob. Chi- Square(9) 0.9999 The residuals for both inflation and economic growth models are homoscedastic as shown in Tables 12 and 13. At 10% level of significance, the null hypothesis-that the residuals are homoscedastic fail to be rejected (Breusch and Pagan, 1979 cited in Uyanto [73]). 1642 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate Table 14. Ramsey Test Inflation Model. Ramsey RESET Test Specification: INF INF(-1) LEND DEP M M(-1) EXCH EX EX(-1) REV DEBT DEBT(-1) CONS C Omitted Variables: Squares of fitted values Value df Probability t-statistic 1.441649 18 0.1666 F-statistic 2.078353 (1, 18) 0.1666 F-test summary: Sum of Sq. df Mean Squares Test SSR 0.003262 1 0.003262 Restricted SSR 0.031512 19 0.001659 Unrestricted SSR 0.028250 18 0.001569 Table 15. Ramsey Test Economic Growth Model. Ramsey RESET Test Specification: ECOG ECOG(-1) LEND DEP M M(-1) EXCH EXCH(-1) EX EX(-1) REV REV(-1) DEBT CONS INF C Omitted Variables: Squares of fitted values Value df Probability t-statistic 0.502110 16 0.6224 F-statistic 0.252114 (1, 16) 0.6224 F-test summary: Sum of Sq. df Mean Squares Test SSR 7.81E-05 1 7.81E-05 Restricted SSR 0.005033 17 0.000296 Unrestricted SSR 0.004955 16 0.000310 By conducting the misspecification test, specifically the Ramsey test RESET test, Table 14 shows that the null hypothesis holds true, as the p-value of 0.1666 is above the 10% significance level. This confirms that the inflation model does not have omitted variables and is correctly specified. Similarly, the p-value of 0.6224 in Table 15 is greater than the 10% significance level, further supporting the null hypothesis’s validity which indicates that the model is free from omitted variables and is well specified (Hendry, 1995 cited in Fuinhas and Marques [74]). The model stability tests indicate that the parameters of the ARDL models remain stable throughout the sample period, as shown by the CUSUM and CUSUM squared tests. The critical boundaries are marked by the red lines at the 5% significance level. Both the inflation model and the economic growth model are stable as clearly demonstrated in Figures 3,4,5, and 6 (Brown et al., 1975 cited in Dritsaki and Stamatiou [66]). 1643 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate -15 -10 -5 0 5 10 15 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 CUSUM 5% Significance Figure 3. CUSUM Test Inflation Model. 1644 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate -0.4 0.0 0.4 0.8 1.2 1.6 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 CUSUM of Squares 5% Significance Figure 4. CUSUM Square Test Inflation Model. 1645 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate -12 -8 -4 0 4 8 12 2006 2008 2010 2012 2014 2016 2018 2020 2022 CUSUM 5% Significance Figure 5. CUSUM Test Economic Growth Model. 1646 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate -0.4 0.0 0.4 0.8 1.2 1.6 2006 2008 2010 2012 2014 2016 2018 2020 2022 CUSUM of Squares 5% Significance Figure 6. CUSUM Square Test Economic. Empirical studies related to the public debt-inflation relationship showed variations. Some research found that public debt positively influences the rate of inflation [75-81]. Other studies found an adverse correlation between the two [81-83]. In fact, the country mentioned, sample duration and estimation technique all affect the results. This study confirmed earlier research by demonstrating a positive long term co-integrated association between public and the rate of inflation. According to Keynes (1936) cited in [4] private consumption is one of the three components of effective demand. The excess of effective demand over the level required for full employment is what causes inflation. This study finds that household consumption affects inflation positively. Additionally, this study demonstrates that inflation and economic growth are adversely correlated over the long term. This supports [84]. 5. Conclusion To determine the factors influencing inflation and how they impact economic growth in Lebanon from 1990 to 2022, this study employs the ARDL approach. The first step in the econometric test was to confirm stationarity. Only deposit interest rate (DEP) and household consumption (CONS) were stationary at level. The rest were stationary at first difference. Under the ARDL assumptions, the study reveals that the long-term effect on inflation from household consumption and public debt is positive and significant. Moreover, governmental debt and household consumption do not have a short-term influence on the rate of inflation. In terms of economic 1647 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1631-1650, 2025 DOI: 10.55214/25768484.v9i6.8207 © 2025 by the authors; licensee Learning Gate growth and inflation, the findings suggest that the inflation rate adversely affects both long-term and short-term economic growth. Overall, awareness of the dynamic relation between pricing levels and overall economic stability requires understanding of inflation and its effect on economic growth. The formulating of fiscal or monetary policy is directly impacted by inflation. Excessive inflation lowers consumer purchasing power and adjusts corporate strategies for capital allocation wages and pricing all of which affect future sustainability of economic growth. Low or stable inflation creates an atmosphere that allows for long term economic growth. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Copyright: © 2025 by the authors. 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