Intro d uction

Consumption behavior is one of the key components in economic dynamics, particularly in developing countries such as Indonesia. Domestic economic activity is closely associated with household spending patterns. These patterns not only reflect prevailing economic conditions but also indicate how households perceive the overall economic environment, including their responses to various ongoing changes. The Consumer Confidence Index (CCI) captures how households assess current economic conditions as well as their expectations for the future1. Being perception-based, movements in the CCI do not always align with conventional macroeconomic indicators such as inflation or exchange rates. Changes in the CCI may occur more rapidly, for instance when households respond to information or perceived economic shifts, even before such changes are reflected in official economic data. The CCI is also closely related to household consumption behavior2. In certain circumstances, shifts in consumer sentiment may be followed by adjustments in spending behavior, such as increasing or restraining consumption. However, such responses are not uniform, as they are still influenced by other factors including income levels and price dynamics. Overall, the CCI is more appropriately interpreted as an indicator of the direction of household economic perceptions rather than a variable that directly reflects changes in actual economic activity3.

From the perspective of expectation theory, economic agents tend to make decisions based on expectations regarding future economic conditions4. In capital markets, the Efficient Market Hypothesis (EMH) proposed by 5 Eugene Fama suggests that stock prices reflect publicly available information and investor expectations. Therefore, changes in inflation, exchange rates, and consumer sentiment may influence stock market movements as market participants respond to new economic information.

Besides perception-based indicators, inflation and exchange rates are also widely used to evaluate overall economic conditions. From the demand side, inflation is associated with changes in prices that affect household purchasing power and consumption behavior. From the supply side, inflation may increase firms’ production and operational costs through higher prices of raw materials, energy, and distribution services6. Meanwhile, exchange rate movements are closely related to firm-level production activities because they affect the costs of imported inputs, production components, and foreign currency-denominated obligations. Firms that rely heavily on imported materials may experience rising production costs during periods of exchange rate depreciation. However, the effects of exchange rate movements may differ across firms depending on their operational characteristics, market orientation, and pricing flexibility7

These conditions are particularly relevant in the consumer non-cyclicals sector, which consists of firms producing essential goods with relatively stable demand. Despite its defensive characteristics, firms within this sector remain exposed to macroeconomic pressures arising from inflation and exchange rate fluctuations. Production and distribution activities in this sector still involve various cost components that are sensitive to changes in prices and exchange rates. Company responses to these pressures may vary depending on pricing strategies, operational efficiency, and prevailing market conditions8. During the post-pandemic recovery period, Indonesia experienced inflationary pressures, exchange rate volatility, and shifts in consumer sentiment occurring within a relatively short period. Although the consumer non-cyclicals sector is generally considered more resilient compared to cyclical sectors, movements in the JKNONCYC index still reflected varying responses to changing macroeconomic conditions and consumer perceptions across periods. This indicates that stock performance in defensive sectors may still be influenced by macroeconomic variables and perception-based indicators, even when demand for essential goods remains relatively stable.

Several previous studies have examined the relationship between macroeconomic variables, consumer sentiment, and stock market performance in Indonesia. In 7 found that exchange rate movements had a significant negative effect on the Composite Stock Price Index (IHSG), while inflation did not show a significant effect. Meanwhile9, reported that investor sentiment and the Consumer Confidence Index significantly affected stock returns during the COVID-19 pandemic period in Indonesia. However, most previous studies focused on broader market indices rather than sector-specific indices such as consumer non-cyclicals. In addition, studies incorporating consumer confidence together with inflation and exchange rates in explaining JKNONCYC movements during the post-pandemic recovery period remain limited. Findings regarding the effects of inflation and exchange rates on stock market performance also remain mixed across sectors and periods. Therefore, this study contributes to the literature by examining both short-run and long-run relationships between the Consumer Confidence Index, inflation, exchange rates, and the JKNONCYC index using the Autoregressive Distributed Lag (ARDL) approach.

Based on these considerations, this study aims to analyze the effects of inflation, exchange rates, and the Consumer Confidence Index on the JKNONCYC index in Indonesia. The ARDL approach is employed to identify both short-run and long-run relationships as well as the adjustment process toward long-run equilibrium.

Met h od

This study employs a quantitative approach using secondary data in the form of monthly time-series data covering the period from January 2022 to December 2024. The selected period represents the post-pandemic recovery phase in Indonesia, characterized by inflationary pressures, exchange rate fluctuations, and shifts in consumer sentiment. The variables used consist of the consumer non-cyclicals stock index as the dependent variable, and inflation, exchange rate, and the Consumer Confidence Index as independent variables. The data are obtained from official publications of authoritative institutions such as the Indonesia Stock Exchange, Bank Indonesia, Statistics Indonesia, Investing.com through a documentation method. All data used are aggregate at the national level; therefore, no sampling technique is applied in this study. Operationally, The JKNONCYC index is used to represent stock price movements in the consumer non-cyclicals sector listed on the Indonesia Stock Exchange. Inflation is measured based on changes in the Consumer Price Index (CPI). The exchange rate is proxied by the Rupiah exchange rate against the United States Dollar, while the Consumer Confidence Index (CCI) reflects household perceptions and expectations regarding economic conditions.

The analytical method employed is the Autoregressive Distributed Lag (ARDL) model to identify both short-run and long-run relationships among variables. This model is selected due to its ability to accommodate variables with different orders of integration, provided that none are integrated of order two, I(2). The inclusion of lag structures in the ARDL model is intended to capture the dynamic relationships among variables, as the effects of macroeconomic variables are not always instantaneous but occur gradually over time. The optimal lag length is determined automatically based on the Akaike Information Criterion (AIC). The analysis begins with a stationarity test using the Augmented Dickey-Fuller (ADF) test to determine the order of integration of each variable, followed by a cointegration test using the Bounds Testing approach. Long-run and short-run estimations are then conducted using the Error Correction Model (ECM) framework to examine the adjustment process toward equilibrium. To ensure model validity and reliability, several diagnostic tests are conducted, including tests for normality, autocorrelation, and heteroskedasticity, as well as model stability tests using the CUSUM and CUSUM of Squares plots over the observation period10.

Result an d Discussion

1. Result

The movement of the JKNONCYC index during the period from 2022 to 2024 generally showed an upward trend with fluctuating patterns. The index reached its lowest point in early 2022 before experiencing a relatively consistent increase throughout 2022 and 2023. This condition reflects the recovery of the consumer non-cyclicals sector during the post-pandemic period. During 2024, the index experienced several corrections and periods of weakening; however, it remained at a relatively higher level compared to the beginning of the observation period. The highest index level occurred at the end of 2024 before experiencing an adjustment in the subsequent period. Overall, the movement of the JKNONCYC index indicates that the consumer non-cyclicals sector maintained relatively strong resilience despite still being influenced by changes in macroeconomic conditions and market sentiment during the observation period.

The shifts in Indonesian public sentiment regarding both present and future economic outlooks between 2022 and 2024 are captured through the Consumer Confidence Index (CCI) trends shown in Figure 2 11.

At the beginning of the period, Consumer Confidence index experienced a sharp decline, reaching its lowest point in March 2022 at 111, which represents the lowest level throughout the three-year observation period. However, this condition was short-lived, as the index surged significantly within the following two months to reach a peak of 128.9 in May 2022. This spike indicates a rapid improvement in consumer expectations within a short timeframe. Following this period, the index tended to move stably within a relatively moderate range through 2024, without revisiting the extreme points seen in early 2022. Overall, this pattern illustrates that the most significant fluctuations occurred at the beginning of the period, while in subsequent years, consumer expectations became more controlled and stable.

During the observation period from 2022 to 2024, the inflation rate exhibited a highly dynamic pattern. Initially, inflation was relatively low at 2.18% in January 2022, but it experienced a sharp and consistent surge, peaking at 5.95% in September 2022. This period marked the most significant inflationary pressure within the three-year span. Following this peak, the trend began to shift toward a gradual decline throughout 2023. By the end of 2024, the situation had stabilized significantly, reaching its lowest point of 1.55% in November 2024. Overall, this pattern illustrates that while 2022 was characterized by high volatility and rising costs, the subsequent two years showed a successful transition toward a more controlled and stable inflationary environment.

1. Analysis of Variable Trends
2. Test Model

This test is conducted using the Augmented Dickey-Fuller (ADF) method to determine the order of integration of each variable. The results of the stationarity test at both the level and first-difference forms are presented in Table 1.

Based on Table 1, all research variables, JKNONCYC, INFLATION, EXCRATE, and CCI, are non-stationary at the level form, as their probability values exceed the 0.05 significance level. After applying the first difference transformation, all variables become stationary, with probability values below 0.05. These results indicate that all variables are integrated of order one, I(1), which satisfies the key requirement for applying the Autoregressive Distributed Lag (ARDL) model.

To establish the most reliable model for this analysis, the selection of the optimal lag length is determined by evaluating various Akaike Information Criterion (AIC) values, as visually summarized in Figure 5.

Table. 2. Bounds Test Result

In the short-run estimation, the coefficient of the Error Correction Term (ECT) is -1.4955 with a probability value of 0.0001. The negative and statistically significant ECT confirms the existence of a long-run cointegration relationship among the variables. The magnitude of -1.4955 indicates a highly responsive speed of adjustment toward long-run equilibrium, implying that shocks from the previous period are corrected within a relatively short time (less than one monthly period).

The long-run ARDL estimation results, which indicate the magnitude and significance of the relationship between the variables over time, are summarized in Table 4.

Based on the long-run estimation results presented in Table 5, the Consumer Confidence Index (CCI) exhibits a coefficient of -0.8645 with a probability value of 0.0258. This indicates that, in the long run, the CCI has a negative and statistically significant effect on the JKNONCYC index. In contrast, the Inflation and Exchange Rate variables have probability values of 0.2773 and 0.3642, respectively (both greater than 0.05), indicating that neither variable has a statistically significant long-run effect on the JKNONCYC index.

1. Stationarity Test
2. Optimal Lag Selection
3. Long-Run ARDL Estimation
4. Model Summary and Diagnostic Tests

To evaluate the robustness and validity of the model, an analysis of goodness of fit and classical assumption tests is conducted. This evaluation includes the coefficient of determination (R-squared), the joint significance test (F-statistic), and diagnostic tests consisting of autocorrelation, heteroskedasticity, and residual normality tests. The results of the goodness of fit and diagnostic tests are presented in Table 5.

To validate the consistency of the long-run and short-run coefficients, stability diagnostics were performed. The results of the model stability test using the CUSUM parameter in Figure 6 and the CUSUM of Squares parameter in Figure 7 can be observed to evaluate the consistency of the model parameters throughout the study period.

Figure . Cusum Test

Figure . Cusum of Squares test

Based on Figure 6 Cusum and Figure 7 Cusum of Squares test, the blue statistic line remains within the critical bounds at the 5% significance level (red lines). This indicates that the parameters of the estimated ARDL (4, 4, 2, 4) model are stable over the observation period from January 2022 to December 2024. This model stability suggests that no significant structural breaks occurred during the study period, despite fluctuations in macroeconomic variables and market sentiment.

1. Discussion

In the short run, at the current period, the Consumer Confidence Index (CCI) has a negative and statistically significant effect on JKNONCYC, with a coefficient of -0.531414 and a probability value of 0.0065. However, at the first lag, CCI shows a positive and significant effect with a coefficient of 0.612667 and a probability of 0.0252, while at the third lag it also remains positive and significant with a coefficient of 0.321390 and a probability of 0.0180. In the long run, CCI has a coefficient of -0.277786 with a probability value of 0.0258, indicating that an increase in CCI significantly reduces the JKNONCYC index.

These results indicate that the effect of CCI on the stock index is dynamic in the short run. An increase in CCI reflects rising optimism among consumers regarding current economic conditions and future economic prospects. However, at the current period, the negative effect suggests a portfolio reallocation from defensive sectors such as consumer non-cyclicals toward more cyclical sectors, which are perceived to offer higher returns when economic growth expectations improve.

Within the framework of the Efficient Market Hypothesis (EMH), information reflected in the CCI is quickly incorporated into stock prices through investor reactions. When CCI increases, investors not only assess current economic conditions but also form expectations about future profit opportunities. This leads to heterogeneous initial market responses before adjustments occur based on real consumption conditions, as reflected in the alternating effects observed across different lags.

This finding is consistent with9 who show that the Consumer Confidence Index has a negative and significant effect on Islamic stock returns in Indonesia. Their study explains that an increase in CCI may be followed by non-fully rational investor behavior, where optimism about economic conditions leads to portfolio adjustments toward other assets or sectors. This suggests that investor sentiment is driven not only by current conditions but also by expectations of future economic developments, which may generate contradictory market responses.

In the long run, the negative effect of CCI on JKNONCYC indicates that after the initial adjustment phase, investors tend to rebalance their portfolios and take profits, reallocating investments toward sectors that are more sensitive to economic growth, thereby reintroducing downward pressure on the consumer non-cyclicals sector.

Based on the ARDL estimation results, inflation exhibits different effects in the short run and long run on the JKNONCYC index. In the short run, inflation is not statistically significant at the current period and the first lag, but shows a negative and significant effect at the second and third lags. In contrast, in the long run, inflation remains statistically insignificant, with a coefficient of 0.034938 and a probability value of 0.2773.

These findings indicate that market responses to inflation shocks do not occur immediately but require an adjustment process before being reflected in stock price movements. An increase in inflation reduces household purchasing power and raises firms’ production costs, thereby potentially weakening corporate performance, particularly in the consumer non-cyclicals sector, which is closely related to essential goods and distribution activities.

This finding is consistent with previous empirical research by12, which shows that inflation has a negative effect on firm performance in the consumer non-cyclicals sector in Indonesia. Rising inflation leads to higher prices of basic goods, which reduces sales volume and subsequently decreases firm profitability and market value.

These results indicate that the effect of inflation is more dominant in the short run, while becoming insignificant in the long run. This is consistent with the Efficient Market Hypothesis (Fama, 1970), which suggests that economic information such as inflation is quickly incorporated into stock prices through investor reactions. However, after the information adjustment process is completed and investors reassess firm fundamentals, the impact of inflation on stock indices becomes less dominant in the long run.

1. Effect of Consumer Confidence Index (CCI) on JKNONCYC
2. Effect of Inflation on JKNONCYC
3. Effect of I Exchange Rate on JKNONCYC

Based on the ARDL estimation results, the exchange rate shows a positive and statistically significant effect in the short run at the current period, with a coefficient of 0.686512 and a probability value of 0.0063, while it becomes insignificant in the subsequent lag. In the long run, the exchange rate has a coefficient of -0.187119 with a probability value of 0.3642, indicating no statistically significant effect on the JKNONCYC index.

During the 2022–2024 period, market conditions were also influenced by the post-pandemic economic recovery, leading investors to focus more on domestic consumption prospects rather than external pressures from exchange rate fluctuations. From the perspective of the Efficient Market Hypothesis (EMH), information regarding exchange rate movements is quickly incorporated into stock prices through investor responses, although the adjustment process is still influenced by expectations of firm fundamentals and domestic economic conditions.

These findings suggest that the impact of the exchange rate is not limited to stock price movements but also reflects broader macroeconomic conditions. This is consistent with13 who find that the exchange rate affects financial stability in Indonesia. Their study explains that rupiah depreciation may have a positive effect through improved economic competitiveness and strengthened real sector performance, but it can also increase financial risks when firms are exposed to foreign currency liabilities. Thus, the effect of the exchange rate is context-dependent and varies according to economic structure and sector characteristics.

In addition, 14 shows that the exchange rate has a significant effect on stock price movements, particularly the IHSG, in both the short run and long run. However, the relationship is not always stable and may vary across periods and economic conditions, indicating that the effect of the exchange rate on the stock market is dynamic.

The positive short-run effect of the exchange rate can be interpreted as a reflection of market optimism regarding the resilience of the consumer non-cyclicals sector in facing economic fluctuations, while the insignificant long-run effect suggests that fundamental factors play a more dominant role in driving the index movement.

This study demonstrates that macroeconomic variables and consumer sentiment exert differing impacts on the JKNONCYC index. Inflation and the rupiah exchange rate are proven not to be long-term determinants of the index; instead, they function merely as risk signals and market sentiment indicators in the short run. This confirms the defensive nature of the consumer non-cyclicals sector against production cost fluctuations and weakened purchasing power. Meanwhile, the Consumer Confidence Index (CCI) is found to be the most dynamic factor triggering sector rotation. Although consumer optimism fundamentally supports corporate performance, in the long run, it encourages investors to reallocate their portfolios toward more aggressive sectors. Consequently, investing in JKNONCYC requires an adaptive strategy that considers economic cycles and market behavior to optimize investment decisions.

Acknowledgments

The author wishes to express sincere gratitude to the academic supervisor for the invaluable guidance, advice, and support provided throughout this research. The author also feels deeply supported by the academic environment at the Faculty of Economics and Business, Universitas Pembangunan Nasional “Veteran” East Java. Furthermore, appreciation is extended to the Indonesia Stock Exchange, Bank Indonesia, BPS - Statistics Indonesia, and Investing.com for providing the essential data used in this study.

Referen ces

2024, doi: 10.29407/nusamba.v9i2.20574.2024, doi: 10.29407/nusamba.v9i2.20574.

1. S. Juhro and B. Iyke, “Consumer Confidence and Consumption Expenditure in Indonesia,” Econ. Model., vol. 89, 2019, doi: 10.1016/j.econmod.2019.11.001.
2. B. B. Tjandrasa and V. I. Dewi, “Determinants of Consumer Confidence Index to Predict the Economy in Indonesia,” Australas. Account. Bus. Financ. J., vol. 16, no. 4, pp. 3–13, 2022, doi: 10.14453/aabfj.v15i4.02.
3. A. Nursari and A. D. Pratama, “Bagaimanakah Kepercayaan Konsumen, Kepercayaan Bisnis dan Konsumsi Rumah Tangga Mempengaruhi Kestabilan Perekonomian Indonesia?,” Owner, vol. 8, no. 1, pp. 902–915, 2024, doi: 10.33395/owner.v8i1.1973.
4. M. A. Djirimu and A. D. Tombolotutu, Ekspektasi Rasional dalam Teori Ekonomi Makro. Deepublish, 2022. [Online]. Available: https://books.google.co.id/books?id=rx8UEQAAQBAJ
5. E. F. Fama, “Efficient Capital Markets: A Review of Theory and Empirical Work,” J. Finance, vol. 25, no. 2, p. 383, 1970, doi: 10.2307/2325486.
6. S. Nurkholifah and M. F. Abdullah, “Analisis Pengaruh Inflasi dan Pertumbuhan Biaya Produksi terhadap Profit Margin pada Perusahaan Food and Beverages yang Go Publik di BEI,” J. Ekon. Pembang., vol. 8, no. 1, pp. 293–306, 2010, doi: 10.22219/jep.v8i1.3604.
7. M. S. Faqih and B. Priyono, “Pengaruh Perubahan Suku Bunga, Inflasi, dan Nilai Tukar terhadap Perubahan Indeks Harga Saham Gabungan (IHSG) Periode 2019–2024,” J. Bus. Adm. Econ. Entrep., vol. 7, no. 2, pp. 139–150, 2025, doi: 10.32834/jbest.v7i2.987.
8. A. Khayati, R. Sari, and A. Giovanni, “Nilai Tambah Modal Manusia dan Keberlangsungan Bisnis Perusahaan Sektor Consumer Non-Cyclicals,” Borobudur Manag. Rev., vol. 2, no. 2, pp. 177–197, 2022, doi: 10.31603/bmar.v2i2.7377.
9. R. Fadhel, F. Adrianto, and M. F. Alfarisi, “Analisis Sentimen Investor terhadap Kinerja Saham Syariah di Indonesia Selama Masa Pandemi COVID-19,” Owner, vol. 6, no. 4, pp. 3579–3591, 2022, doi: 10.33395/owner.v6i4.1183.
10. D. N. Gujarati and D. C. Porter, Basic Econometrics. McGraw-Hill Education, 2008. [Online]. Available: https://books.google.co.id/books?id=zJlDPgAACAAJ
11. Investing.com, “Indonesia SE Consumer Non-Cyclicals Historical Data,” 2026. [Online]. Available: https://id.investing.com/indices/indonesia-se-consumer-noncyclicals-historical-data
12. Bank Indonesia, “Metadata Survei.” [Online]. Available: https://www.bi.go.id/id/statistik/metadata/survei/default.aspx
13. Bank Indonesia, “Data Inflasi Indonesia,” 2026. [Online]. Available: https://www.bi.go.id/id/statistik/indikator/data-inflasi.aspx
14. Bank Indonesia, “Kurs Transaksi BI.” [Online]. Available: https://www.bi.go.id/id/statistik/informasi-kurs/transaksi-bi/default.aspx
15. D. Pangestuti and A. P. Said, “Analisis Pengaruh Pertumbuhan Penjualan, Profitabilitas, Risiko Pasar, dan Inflasi terhadap Nilai Perusahaan Sektor Consumer Non-Cyclicals,” J. Nusant. Apl. Manaj. Bisnis, vol. 9, no. 2, pp. 521–539,
16. B. A. Winpor and A. Hidayat, “The Effect of Interest Rates, Exchange Rates, and Foreign Direct Investment on Financial Stability in Indonesia,” Argumenta Oeconomica Cracoviensia, no. 1–2(26–27), pp. 49–72, 2024, doi: 10.15678/aoc.2024.2603.
17. S. Ranto, “Pengaruh Jangka Pendek dan Jangka Panjang Variabel Makro Ekonomi terhadap IHSG di Bursa Efek Indonesia dengan Pendekatan Error Correction Model (ECM),” J. Deriv. J. Mat. dan Pendidik. Mat., vol. 6, no. 1, pp. 12–24, 2019, doi: 10.31316/j.derivat.v6i1.332.