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The effectiveness of ultra-loose monetary policy in a high inflation economy: a time-varying causality analysis for Turkey

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Abstract

The highest rate of inflation was observed as countries faced increasing prices for food and energy, primarily due to supply disruptions caused by the COVID-19 pandemic and the war in Ukraine. In such challenging times, interest rate-based monetary policy remains an important issue for fighting inflation. From a policy perspective, central banks all over the globe tighten their monetary policy stance to cool inflation. Arguably, Turkey opted for an ultra-lose monetary policy via very low interest rates in response to high inflation. Drawing on the Turkish experience, we tackle the evolution of the Turkish central bank’s operations in the face of high inflation, providing further details on how ultra-loose monetary policy implementation can be extremely challenging in a highly inflationary economy. We extend the existing body of literature by employing the time-varying Granger causality model proposed by Shi et al. (J Time Ser Anal 39:966–987,2018; J Financ Econom 18:158–180, 2020). Using monthly data (2005:01 to 2022:01), we examine the links between interest rates, inflation, and exchange rates to detect possible changes across various time horizons. The major finding of this study explores the significant episodes of causality by detecting the origination date of causality starting from 2018 toward 2021. This finding confirms that August 2018 and its repercussions on the sharp currency depreciation and high Turkish inflation are pivotal moments to understand the nature of Turkey’s economic growth model and the impact of monetary policy in the ongoing economic crisis that hit Turkey harder. Our results reveal that a poorly managed country’s interest rate decisions can be disastrous for the exchange rate movements and inflation dynamics, whereas the conclusion is that there are limits to what central banks can do.

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Data availability

The datasets used and/or analyzed during the current paper are available from the corresponding author upon reasonable request.

Notes

  1. A growing number economists have argued that global factors such as commodity price shocks and supply disruptions play a major role in driving the surge in global inflation, pointing out the recent inflation has mostly supply-side origins. (See, e.g., Storm (2022) for a detailed analysis of the key drivers of recent inflation.)

  2. Throughout this study, we employ the terms "Turkish central bank," "Central Bank," and "Central Bank of the Republic of Turkey (CBRT)" interchangeably.

  3. The exchange rate pass-through effect (ERPE) is the key to understanding the importance of exchange rates on price in domestic and export markets. It implies that exchange rate movements reflect on prices mainly through exported goods.

  4. The Turkish lira has been the most depreciating currency among emerging market economies. The Lira has lost more than 60 percent of its value against the US dollar. With the sharp Lira depreciation, the consumer price index (CPI) inflation is skyrocketing in Turkey, hovering at around 83 percent in 2022. This level of inflation is the highest reading over the last 20 years. Furthermore, Turkey’s current account trade deficit is the largest in the world’s emerging markets, noting that the current account deficit went up from $1.19 billion in June 2021 to $3.46 billion in June of 2022 (CBRT 2022). Much of the country’s imports are financed with foreign debt, and it also has been experiencing economic fragility with high private debt denominated in the US dollar. Financial experts have highlighted that recent events in Turkey have led to an escalation in the foreign-exchange liabilities of the non-financial corporate sector, particularly in US dollars. Additionally, it is worth noting that Turkey has been required to roll over approximately $200 billion of foreign debt on an annual basis. (See, for example, Tastan (2021)).

  5. In theory, the nexus between interest rate and exchange rate nexus is to a great extent explained by interest rate parity. The differences between domestic and international interest rates determine the exchange rate. This is because in financial markets the yield differences between countries cause capital flows. If the domestic interest rates are higher than international interest rates, then the country will receive capital flows (capital inflow) due to yield differences, which in turn leads to depreciation of the exchange rate. On the other hand, if the domestic interest rate is lower than the international rates, then the local currency will depreciate since the capital will leave the country (capital outflows) which in turn leads to an increase in the value of the exchange rate. In the context of the monetary transmission mechanism, central banks can affect exchange rates given that they determine their policy interest rates. For instance, if the central bank raises the policy interest rates, the domestic currency will start to appreciate due to the incentives for capital inflows based on the interest rate parity, which in turn leads to depreciation of the exchange rate.

  6. For a full statement on May 28, see CBRT (2018b).

  7. On December 16, 2021, the Ministry of Treasury and Finance released a written statement to introduce the basic fundamentals of the new Türkiye Economy Model. To see the statement, MTF (2021).

  8. See full statement on newsletter of the Presidency of the Republic of Turkey—Investment Office IOTurkey (2022).

  9. President Erdoğan explained the details of new economic model on December 25, 2022 (Hurriyet 2021).

  10. Note that there is no causality analysis specifically pertaining to the industrial production variable. Nevertheless, it is included in our analysis to mitigate any potential model specification error. Consequently, we proceed with an examination of the relationship between industrial prices, interest rates, inflation, and exchange rates in Turkey by employing a four-variable VAR model.

  11. We consider two interest rate variables for the causality analysis. The main interest rate is the Weighted Average Cost of the CBRT Funding to potentially represent the central bank policy rate as in (Binici et al. 2019). Accordingly, this rate is subject to variation based on the funding composition of the central bank. Considering the total funding consists of two components, namely weekly funding and overnight funding, the CBRT’s weighted average funding rate can be represented by the following expression: i = (weekly repo*weekly repo rate + O/N funding*O/N funding rate)total funding. While the direct source of data can be obtained on the CBRT’s website CBRT (2023), for the period between 2005 and 2011, we consider the weekly funding and overnight funding that are available during the selected month. In the context of market interest rates (MRK), our methodology involves the utilization of the average rates observed in both commercial and consumer loans. By incorporating data from these two segments, we obtained market interest rates by the following formula: \(i_{market}\) = (\(i_{commercial loans}\) + \(i_{consumer loans}\))/2. It is important to note that in conducting the causality analysis, the model incorporates one of the interest rates as a substitute variable. Hence, our analysis remains grounded in a four-variable VAR model.

  12. The results of this test are not reported to conserve space.

  13. It is important to note that Shi et al. (2018, 2020) have demonstrated that the recursive evolving method exhibits superior performance in detecting changes when compared to the other two approaches. Following the empirical strategy outlined by Shi et al. (2018, 2020), a minimum window size of 41 (equivalent to a 3-year period) is defined, and the Bayesian information criterion (BIC) is employed to determine the lag length, with a maximum lag order of 12, for the entire sample period. The selected lag length is subsequently applied to the sub-sample models. Additionally, to maintain consistency with Shi et al. (2020), the overall size is controlled to be 5% over a 1-year period. Figure 9 presents the results of the Wald test statistics, illustrating potential causal effects from the market interest rate to inflation (panal-a) and the causality effects from exchange rates to market interest rates (panel-b) along with their respective bootstrapped critical values. Moreover, the analysis accounts for heteroskedasticity by employing consistent estimation methods that make assumptions regarding the variance of the vector autoregressive (VAR) errors. All sequences of the test statistics cover the period from April 2008 to January 2022, and the figures include the dates of causal episodes whenever the test statistic sequence surpasses the 5% critical value sequence.

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Authors and Affiliations

  1. Department of Economics, Management and Quantitative Methods, University of Milan, Milan, Italy

    Mehmet Ulug

  2. Department of Economics, Akdeniz University, Antalya, Turkey

    Sayım Işık

  3. Department of Econometrics, Akdeniz University, Antalya, Turkey

    Mehmet Mert

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  1. Mehmet Ulug
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  2. Sayım Işık
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MU helped in project administration, software, writing original draft, writing—review & editing, visualization. SI contributed to investigation, resources, data curation, writing original draft. MM was involved in methodology, writing original draft.

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Ulug, M., Işık, S. & Mert, M. The effectiveness of ultra-loose monetary policy in a high inflation economy: a time-varying causality analysis for Turkey. Econ Change Restruct 56, 2855–2887 (2023). https://doi.org/10.1007/s10644-023-09535-3

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