Information about Asia and the Pacific Asia y el Pacífico
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Thailand: Selected Issues

International Monetary Fund. Asia and Pacific Dept
Published Date:
June 2018
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Thailand: Synergies Between Monetary and Macroprudential Policies1

A dynamic stochastic general equilibrium (DSGE) model tailored to the Thai economy is used to explore the performance of alternative monetary and macroprudential policy rules when faced with shocks that directly impact the financial cycle. In this context, the model shows that a monetary policy focused on its traditional inflation and output objectives accompanied by a well targeted counter-cyclical macroprudential policy yields better macroeconomic outcomes than a lean-against-the-wind monetary policy rule under a wide range of assumptions.

A. Introduction

1. A key objective of the Thai monetary authorities is to lift inflation back to target without unduly stimulating household debt and housing prices. Over the last decade, Thailand has seen a significant increase in household debt (Figure 1). At the same time, low interest rates in advanced economies and a strong external position have contributed to exchange rate appreciation and a drop in the inflation rate below the target range. Even though growth in household debt in percent of GDP started declining and interest rates in advanced economies began rising, the level of household debt remains high and inflation continues to show weak dynamics.

Figure 1.Thailand: Housing Market Development

2. Macroprudential measures can be a useful complement to monetary policy in addressing potential pockets of vulnerability to financial stability. While monetary policy provides only one instrument (interest rate), counter-cyclical macroprudential tools could provide a useful complement, especially when real and financial cycles do not coincide. The Thai authorities already implemented three main macroprudential measures: (i) limits on loan-to-value ratio in the property market, (ii) limits on credit card and personal loans, and (iii) dynamic loan loss provisioning.2 Recent empirical studies suggest that some of these measures have been effective in stabilizing credit cycles.3 However, it remains an open question which type of policy combination of monetary and macroprudential policies would be most effective in dealing with both real and financial cycles. For instance, there have been active debates on whether monetary policy should address financial stability or focus on inflation and output stability. The type of macroprudential policy measures could also make a substantial difference in the outcome of its combination with monetary policy.

3. Using a DSGE model tailored to the Thai economy, this paper sheds light on the following issues: (i) the combination of monetary and macroprudential policies that would be most effective for Thailand in dealing with both real and financial cycles; and (ii) the appropriate choice of macroprudential tool in such policy combination.

B. Model Features and Key Assumptions

4. The joint effects of monetary and macroprudential policies are assessed using an open-economy DSGE model. The analysis aims to explore various conditions under which the use of macroprudential measures can (or cannot) improve macroeconomic outcomes within a plausible (including counterfactual) range of parameters and assumptions. Since there are a growing number of DSGE models that incorporate macroprudential measures in a variety of ways and different models focus on different aspects of financial frictions and economic environment (Box 1), choosing a relevant model and tailoring it to the current context of the Thai economy is crucial. It is also important to note that quantitative implications may be highly dependent on model specifications and calibrations.

5. To tailor to the Thai economy, the model incorporates a fully specified banking sector, household and corporate debt, and external borrowing.4 It is based on a New Keynesian DSGE model for small open economies with price rigidities and financial frictions. Under these frictions, inflation stability and financial stability improve welfare. The banking sector, which intermediates funds from patient households to impatient households and entrepreneurs, plays a crucial role for policy transmission.5 The brief descriptions of private economic agents, namely households, entrepreneurs, and banks, are as follows (Figure 2 depicts the relationships between agents in this economy).

  • There are two types of households, patient (with a lower intertemporal discount rate) and impatient,6 who both derive utility from consumption, leisure, and housing. In equilibrium, the patient households save part of their income, which is invested in domestic bank deposits and foreign bonds. Impatient households end up borrowing to consume and purchase houses.

  • Entrepreneurs borrow from domestic banks and from abroad to purchase capital. They also hire labor and produce goods that are then sold to retailers who subsequently sell to the consumers, capital producers, and foreign markets in a monopolistically competitive environment.

  • Banks can lend to the government, entrepreneurs, or households. Interest rates are sticky because banks face quadratic costs associated with changes in interest rates. At the same time, bank borrowing is subject to macroprudential measures.

Figure 2.Thailand: Model Overview

Source: IMF staff.

6. Monetary and macroprudential policies are described by policy reaction functions. Two separate policy functions are incorporated: one for the monetary policy interest rate that follows a Taylor rule; and the other for a macroprudential policy measure, specifically either a cap on household loan-to-value (LTV) ratio or a minimum bank capital adequacy ratio (CAR). For each policy reaction function, we consider two variants. The two variants of the Taylor rule are as follows:

a. Standard Taylor rule—focused on inflation and output gap

i = α1 × inflation gap + α2 × output gap

where i is the policy interest rate, inflation gap is the difference between actual inflation and the target, and output gap is the difference between actual and potential output.

b. Modified Taylor rule—focused on inflation, output, and credit gaps

i = α1 × inflation gap + α2 × output gap + α3 × credit gap

where credit gap is the difference between the actual stock of household credit and its steady-state level.7

The two variants for a macroprudential measure are as follows:

  • a. Constant LTV (or CAR) rule: The cap on LTV applied to household credit (or the minimum CAR applied to bank credit) is kept constant.

  • b. Countercyclical LTV (or CAR) rule: The cap on LTV applied to household credit decreases (or the minimum CAR applied to bank credit increases) as the stock of household (or bank) credit increases relative to its steady-state value.

7. The performance of policy combinations is evaluated in terms of the volatilities of inflation, output, and housing loans in response to specific types of shocks. The following three combinations of policy rules are compared: (i) a standard Taylor rule with a LTV (or CAR) rule, (ii) a standard Taylor rule with a counter-cyclical LTV (or CAR) rule, and (iii) a modified Taylor rule with a constant LTV (or CAR) rule.8 As relevant types of shocks faced by the Thai economy, a negative world interest rate shock (monetary easing in advanced economies) and a positive shock to domestic housing demand are considered.

C. Results

8. A counter-cyclical LTV rule performs better than the modified Taylor rule in response to a negative world interest rate shock. A negative world interest rate shock causes appreciation pressure of the domestic currency and triggers domestic monetary easing, which can lead to housing market overheating (Figure 3). The growth of housing loans is contained to a similar extent under both the counter-cyclical cap on LTV ratio and the modified Taylor rule.9 However, the negative impact of the shock on inflation and output is much larger under the modified Taylor rule than the counter-cyclical LTV rule. As a result, the modified Taylor rule requires a larger cut in the nominal interest rate while the reduction in the real interest rate is relatively small. Therefore, the counter-cyclical LTV rule performs better in terms of stabilizing inflation, output, and housing loans.

Figure 3.Thailand: Responses to a Negative World Interest Rate Shock

Source: IMF staff calculations.

9. A similar result is obtained in the case of a positive housing demand shock (Figure 4). With the counter-cyclical LTV rule, the growth of housing loans is contained without raising the nominal interest rate. By contrast, raising the interest rate following the modified Taylor rule causes a substantial decline in inflation and output while insufficiently containing growth in housing loans.

Figure 4.Thailand: Responses to a Positive Housing Demand Shock

Source: IMF staff calculations.

10. The above results are robust to a wide range of parameter values. For instance, when inflation is less sensitive to output volatility (i.e., the slope of Philips Curve is flatter) compared with the benchmark model, the performance of the modified Taylor rule in terms of stabilizing inflation gets closer to, but does not get better than, that of the counter-cyclical LTV rule. This implies that the limited effectiveness of monetary policy on inflation does not necessarily justify the reaction of monetary policy to financial stability concerns. Similarly, some impairment of the monetary policy transmission in the banking sector (e.g., lower pass-through to the loan interest rate) does not change the result that the counter-cyclical LTV rule performs better than the modified Taylor rule.

11. Broader macroprudential measures could perform worse than the modified Taylor rule. If a targeted macroprudential measure such as the household LTV cap is not available and instead a broader measure such as counter-cyclical bank minimum capital adequacy ratio (CAR) is used, the performance of the latter is, in some cases, worse than the modified Taylor rule. In the case of a negative world interest rate shock, the counter-cyclical CAR ‘overkills’ the growth of housing loans (without sufficiently dampening corporate loans), which leads to a more severe reduction in output compared with the modified Taylor rule. In the case of a positive housing demand shock, however, the counter-cyclical CAR still performs better than the modified Taylor rule. Therefore, the appropriateness of monetary policy reaction to financial stability concerns depends on the availability of targeted macroprudential measures as well as the nature of shocks faced by the economy.

12. The above findings should be interpreted in context. As noted above, targeted macroprudential measures may not always be available. A number of factors may limit availability, such as reliable data, resources for implementation, and jurisdictional constraints. At the same time, cases of weak effectiveness or leakage of macroprudential measures are relatively uncertain and untested. It is also important to note that different types of shocks from those considered above— shocks to the world interest rate and domestic housing demand—may change the above conclusion.

D. Conclusion

13. Targeted macroprudential measures can provide a useful complement to monetary policy in the current context of the Thai economy. Active use of targeted macroprudential measures, to the extent it is available, is likely to achieve better macroeconomic outcomes by allowing monetary policy to focus on inflation and output stabilization while effectively containing financial risks from rising housing loans.

Box 1.Monetary and Macroprudential Policies in DSGE Models

Monetary policy rules that react to financial stability concerns have been studied extensively in recent DSGE models. Standard monetary policy rules that react to inflation and output could lead to growing financial risks under financial frictions (such as collateral borrowing constraints), in which case a monetary policy that also targets financial stability by “leaning against the wind” could be welfare improving. DSGE models compare this benefit with the cost from short-term deviations from inflation and output targets and the corresponding welfare losses. While some models strongly support the case for leaning against the wind (e.g., Gambacorta and Signoretti 2014), other models show that the implied deviations from standard policy rules are quantitatively small (e.g., Curdia and Woodford 2010). Moreover, the case for leaning against the wind may be even weaker in small open economies, where the impact of such policy on international capital flows may exacerbate macroeconomic and financial stability concerns.

More recent DSGE models incorporate various types of macroprudential policy and study its relationship with monetary policy. These models typically find that monetary and macroprudential policies are complements rather than substitutes, in the sense that it is optimal to use these policies together rather than use one policy to achieve the same outcomes as the other (e.g., Angelini et al. 2014). Macroprudential policy could help alleviate tensions between monetary and financial stability objectives because real and financial cycles are not always synchronized and macroprudential policy, especially when targeted at addressing specific financial risks, is generally more effective than monetary policy in dampening financial cycles at a lower cost to output.

The relationship between monetary and macroprudential policies is, in general, highly dependent on the nature of shocks and financial frictions.1 Many recent models suggest that it is optimal to mainly use macroprudential policies in a wake of financial shock that leads to financial stability concerns. By contrast, in response to a (positive) productivity shock, limiting credit by tightening macroprudential policies may be misguided and runs counter to accommodative monetary policy for supporting inflation. The latter conclusion, however, could be reversed if lending by individual banks endogenously affect overall financial riskiness even in the case of a non-financial (productivity) shock, which could make tight macroprudential policies optimal.

1IMF (2012) discusses this issue extensively.

    AnandR.DelloroV. and PeirisS. J.2014A Credit and Banking Model for Emerging Markets and an Application to the PhilippinesProceedings of the 2014 BSP International Research Conference Issue 2 (Manila: Bangko Sentral ng Pilipinas).

    AngeliniP.NeriS. and PanettaF.2014The Interaction between Capital Requirements and Monetary PolicyJournal of Money Credit and Banking46(6) pp. 10731112.

    Bank of Thailand2017Macroprudential Framework: The Case of Thailand.” in Macroprudential frameworks implementation and relationship with other policies BIS Paper No. 94339348.

    CorbachoA.PeirisS. J. and SaenzM.2018Macroeconomic Policy Synergies for Sustained GrowthChapter 9 The ASEAN Way (forthcoming).

    CurdiaV. and WoodfordM.2010Credit Spreads and Monetary PolicyJournal of Money Credit and Banking42 (S1) pp. 335.

    GambacortaL. and SignorettiF. M.2014Should Monetary Policy Lean against the Wind?Journal of Economic Dynamics and Control43 (June) pp. 14674.

    GeraliA.NeriS.SessaL. and SignorettiF. M.2010Credit and Banking in a DSGE Model of the Euro Area.” Journal of Money Credit and Banking42 (6) pp.10741.

    International Monetary Fund2012The Interaction of Monetary and Macroprudential PoliciesPolicy PaperDecember (Washington: International Monetary Fund).

    International Monetary Fund2017Household Debt and Financial StabilityChapter 2 Global Financial Stability ReportOctober (Washington: International Monetary Fund).

    PongsaparnR.NudamR. and WongwacharaW.2017Macroprudential Policy: Its Role Effectiveness and Interaction with Monetary Policy” Focused and Quick (FAQ) Issue 121 (Bangkok: Bank of Thailand).

Prepared by Ichiro Fukunaga and Manrique Saenz.

Bank of Thailand (2017) provides an overview of Thailand’s macroprudential framework.

Pongsaparn et al. (2017) shows that the Bank of Thailand’s measures on LTV ratio have been effective in moderating housing credit growth. In the global context, a cross-country panel regression analysis of the effects of macroprudential measures on household credit growth across advanced and emerging market economies, including Thailand, is reported in the October 2017 GFSR Chapter 2, Box 2.5 (IMF, 2017).

The framework of Anand, Delloro, and Peiris (2014) is extended to incorporate housing sector and household debt, following Gerali et al. (2010). Details of the model will be explained in the forthcoming working paper.

The banking sector in the model encompasses all types of financial intermediaries (including Specialized Financial Institutions) and does not distinguish different mandates and business models among them.

“Impatient households” can also be interpreted as liquidity-constrained households in this model.

Using some alternative financial gaps, including a house price gap, does not change the results substantively.

Another possible combination of policy rules, namely a modified Taylor rule with a counter-cyclical LTV rule, is examined in Corbacho et al. (2018). Its outcomes fall in the middle of those of (ii) and (iii).

For illustrative purpose, we set some large values to the parameters of the policy responses to credit gaps in the counter-cyclical LTV rule and the modified Taylor rule.

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