Chapter

Chapter 10. Czech Republic: Transition to the Frontier

Author(s):
Tobias Adrian, Douglas Laxton, and Maurice Obstfeld
Published Date:
April 2018
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Author(s)
Rania Al-Mashat Kevin Clinton Douglas Laxton and Hou Wang

The Czech experience with inflation targeting thus illustrates that the ultimate purpose of inflation targeting is not to announce inflation targets and then hit them mechanically. It is a mistake to confuse inflation targeting with inflation obsession. The aim is to design a rule-based monetary policy framework characterized by a high degree of transparency and accountability.—Z. Tûma, Governor of the Czech National Bank (2003)

Monetary policy in the Czech Republic moved in less than 10 years from a de facto fixed exchange rate to the frontiers of inflation-forecast targeting.1 This chapter describes the evolution of monetary policy since the revolution of 1990 and how inflation-forecast targeting provided the economy with a firm nominal anchor.

Soon after the collapse of an exchange rate peg in 1997, the central bank adopted inflation targeting. It was a controversial decision, given the concerns at the time about objectives other than inflation control, about current inflation rising above 10 percent, and about the entrenched inflation psychology, and given the doubts about the effectiveness of monetary policy in an economy still in transition. Moreover, the central bank did not have an adequate internal setup to pursue an inflation target. A rapid fall in the inflation rate before 2000 nevertheless boosted the credibility of the new approach. As this was happening, the Czech National Bank (CNB) moved with due speed to establish a forecasting and policy analysis system, with an appropriate forecasting model. In 2002, policy switched from a basic, short-term approach to flexible, medium-term inflation targeting. The new regime used model-based forecasting and policy analysis. In recent years, the credibility of Czech monetary policy allowed the central bank to use an innovative exchange rate strategy to stabilize the economy in the face of disinflationary pressures emanating from other parts of the European Union, and to raise inflation to the 2 percent target. And the CNB has itself become an important provider of international technical assistance on monetary policy.

IMF technical assistance is also part of the story. After the Velvet Revolution opened the door to market-oriented reform, the State Bank of Czechoslovakia recognized the need for radical change to equip the institution for the job of monetary policy in a market economy. To help, the IMF assembled a team of staff members and specialists from various central banks, including the Bank of Canada, the Austrian National Bank, the Bank of Italy, and Norges Bank. They advised on the appropriate structure for all major areas of central banking, including monetary policy analysis and strategy, money markets and policy operations, and foreign exchange operations.

Following the division of the country in 2003, in support of the ongoing IMF program, the Bank of Canada contributed bilateral assistance to the CNB, providing training in Ottawa on money markets, monetary policy operations, model building, and policy strategy, and on the process of decision-making. Personnel from the CNB shared offices with Bank of Canada counterparts and attended key meetings over a period of weeks. Visiting CNB staff included money market traders who sat at the open-market operations desk, and senior managers who observed, from a policymaker level, the assembly of inputs of information for policy decisions and attended forecast and monetary policy committee meetings. The visit gave them insight into an effectively operating forecasting and policy analysis system for inflation targeting.

Recent Czech Monetary Policy

1991–97: De Facto Fixed Exchange Rate

Until 1997 the CNB ran monetary policy based on three pillars: a target for broad money growth, a one-year-ahead inflation-reduction objective, and a fixed exchange rate. In practice, the fixed exchange rate dominated, resulting in a de facto fixed exchange rate regime. This was a stabilizing factor for economic decision during the uncertainties of the economic transformation.2 As long as capital mobility remained limited, monetary policy had a degree of independence to pursue the money growth target, despite the fixed exchange rate. But within a few years, increasing international financial integration exposed the “impossible trinity”: the incompatibility of simultaneously open capital markets, a fixed exchange rate, and an independent monetary policy.

The three pillars never provided a firm nominal anchor. Inflation got stuck in the high single digits. In the mid-1990s, heavy capital inflows forced the CNB to accumulate a growing stock of foreign exchange reserves. The central bank tried to sterilize the monetary impact through the sale of bonds, which placed a burden on the budget since Czech interest rates were much above the rates on the reserve assets. Moreover, the sterilization operations were insufficient to prevent inflationary increases in money supply.

To deter further volatile inflows, the CNB widened the tolerance band around the exchange rate peg to ±7.5 percent in 1996. However, ample supplies of liquidity, combined with inadequate banking regulation and supervision and lax lending standards, led to a credit bubble. Much of the lending covered losses in former state enterprises that bankers perceived to be too big to fail. The expansion of credit overheated the economy, one symptom of which was a large current account deficit.

The economic imbalances and financial weakness were unsustainable. Contagion from the Asian financial crisis and domestic political instability triggered capital flight in 1997. The CNB used 20 percent of Czech foreign currency reserves to defend the exchange rate peg, and hiked the policy interest rate from 12 percent to 26 percent—the one-week interbank rate peaked at 75 percent. Even so, the peg had to be abandoned, and the exchange rate depreciated 13 percent. As the impaired balance sheets of the banks became apparent, a full-blown banking crisis erupted. Real GDP decelerated, and inflation was well above the typical level in the European Union, and rising.

In the aftermath of the collapse in confidence, the CNB attempted a managed float, without a clear nominal anchor to keep inflation expectations under control. However, Czech policymakers were aware of the need for a domestic monetary standard to replace the fixed exchange rate, and they had noted the success of inflation targeting in several advanced economies.3 As noted, several of them had witnessed its implementation in Canada. It did not take long for the central bank to decide in favor of inflation targeting for the nominal anchor.

But this decision was neither easy nor uncontroversial. Economists debated whether inflation targeting could work in a country that was still far from completing the transition to a market economy. Many feared that the Czech Republic did not satisfy so-called preconditions for the regime. Political support for inflation targeting was limited, and the banking system remained fragile. Furthermore, the central bank had focused on the analysis of monetary aggregates, the exchange rate, and the balance of payments, and did not have the resources appropriate for the macroeconomic forecasting and analysis required for inflation targeting.

Economic forecasting, meanwhile, was hindered by inadequate data series, structural shifts, and uncertainties about the transmission mechanism. Decision-making processes were not well-structured; for example, senior-level meetings would include time debating objectives versus how to adjust instruments to achieve objectives. The credibility of an objective for stable, low inflation was an issue because the population was accustomed to inflation in the high single digits, and was expecting sporadic jumps in the prices of various essential services as a wide range of controlled prices—including rents and utilities—were to be liberalized in the years just ahead. The market environment was still incomplete after a half-century of repression, and the effectiveness of monetary policy in the control of inflation was untested.

Despite these uncertainties, in early 1998 the CNB introduced inflation targeting with an ultimate inflation target of 2 percent and a sequence of interim targets for inflation reduction. Since the CNB has goal and instrument independence, it could install the new regime without a lengthy political consultation. In adopting inflation targeting, the central bank took the lead in an atmosphere of doubt, confusion, and financial distress.

Perhaps not surprisingly, the announcement was met with widespread skepticism. Within the central bank itself, there was uncertainty about the reliability of the transmission of conventional monetary policy in view of the ongoing transformation of the economy, sparse macroeconomic data, and the lack of an appropriate forecasting and policy analysis system and models. Some policymakers worried that the central bank would be unable to make good on a commitment to durable inflation reduction, especially in view of the entrenched inflation mentality, the demands for high wage increases in current negotiations, and the eventual need for firms to restore normal profits.

Macroeconomic theory, however, supported by evidence from recent disinflation episodes in the advanced economies, suggested a more sanguine outlook. First, since the steep postcrisis recession and credit squeeze would alone open a disinflationary gap, without the need for further tightening by the CNB, the uncertainties—and probable weaknesses—of the transmission mechanism would not be a material factor in the early phases.

Indeed, in view of the widening output gap and the credit crunch brought on by the banking crisis, there was a high risk that inflation would fall more quickly than the interim targets envisaged—as had happened in Canada, New Zealand, and Sweden. Second, wage settlements tend to be a lagging indicator; they would moderate during the slowdown because of depressed profits and the inability of employers to pass on increased costs given the slack in the economy. And third, the procyclical rebound of productivity in the eventual recovery would hold unit labor costs down and promote a return to normal profitability without a resurgence of price inflation.

1998–2001: Inflation Targeting without a Forecasting and Policy Analysis System

For the most part, inflation targeting turned out reasonably well from the outset. The CNB handled the price decontrol problem by defining the initial inflation reduction targets in terms of net inflation—that is, consumer price index (CPI) inflation excluding the prices affected by the lifting of controls. It listed other special factors that might affect the inflation rate from year to year and that would justify a deviation from the announced targets. It recognized the risk of undershooting the target, announcing that such an outcome would represent unexpectedly rapid progress to the ultimate target and therefore justify a downshift in the target trajectory, rather than attempting to push inflation back up to the interim path originally announced. As it turned out, this risk did materialize—and the steep decline in inflation grabbed the public’s attention and gave the credibility of the CNB’s inflation targeting a needed boost. This experience resonates with the theme in Chapter 3 that when policy is confronted with a credibility problem, an assertive policy stance—which may result in a temporary under- or overshooting of target—can have a salutary, constructive impact on expectations.

Aspects of the fledgling regime, however, did call for improvement. In the absence of a forward-looking framework for policy analysis, policymakers focused excessively on current economic outcomes and were slow to take policy action in anticipation of projected future developments. Failing to take adequate account of the disinflationary impact of the output gap and credit crunch, the CNB kept interest rates too high for too long (Figures 10.1). While the faster-than-intended drop in inflation helpfully brought down long-term expectations, it came at the short-term cost of a deep slowdown and high unemployment, which put the CNB’s independence into political jeopardy.4 Learning from this, the CNB moved with all due speed to set up a forecasting and policy analysis system for forward-looking, flexible inflation targeting and to adopt a more transparent approach to monetary policy communications.

Figure 10.1.Nominal and Real Interest Rates, 1993–2017

(Percent, per year)

Sources: Czech National Bank; Czech Statistical Office; and Haver.

Note: Last observation: 2017:Q4.

2002–07: Inflation-Forecast Targeting with a Forecasting and Policy Analysis System

In setting up the forecasting and policy analysis system, the CNB’s collaboration with the IMF again proved useful. IMF staff members had already helped to design and put to work such frameworks at the Bank of Canada and the Reserve Bank of New Zealand.5 They helped the CNB staff develop an appropriate core monetary policy model (QPM-gap), with forward-looking, model-consistent expectations, and with policy represented by an endogenous short-term interest rate. The specification put a high priority on credible simulation properties, with theoretically plausible responses to shocks. To this end, the model builders calibrated the parameters from a broad range of evidence in small open economies, rather than using traditional econometric estimation, which was not in any case feasible in the Czech Republic at the time, due to the very short time series for the relevant data. In 2002, the forecasting and policy analysis system was ready to go in support of an explicit inflation-forecast-targeting framework with flexible exchange rate.6 This allowed a considerable increase in transparency, as the CNB was now able to make policy informed by an explicit model, the main properties of which reflected standard economic theory. Over time, this would become comprehensible and credible to financial markets and the public.

Work on the forecasting and policy analysis system benefited from the clarification provided by Svensson (1997), which showed that efficient flexible inflation targeting amounted to inflation-forecast targeting. The argument is that the central bank’s inflation forecast represents an ideal intermediate target to manage and communicate the short-term output-inflation trade-off. That is, in the context of returning inflation to its long-term target rate following a shock, the central bank simulates the possible paths available to it and decides on one that accounts for the trade-off between the costs of forecast inflation being off target and the costs of a significant output gap.7 This insight underlined the importance to policymaking of a systematic process to forecast the economy and to map the transmission channels between instruments and objectives in a credible macro-economic model. The CNB would also have to adapt its organizational structure to support the provision of relevant macroeconomic analysis to policymakers. This included the internal and external communications necessary for transparency and accountability.

The Czech economy performed well over much of the 2000s, as did many other economies. Output grew strongly and unemployment fell gradually, from over 7 percent to under 5 percent (Figure 10.2). Longer-term inflation expectations became well anchored (Figure 10.3).

Figure 10.2.Unemployment Rate and Real GDP Growth, 1993–2017

(Percent)

Sources: Czech Statistical Office and Haver.

Note: Last observation: 2017:Q4.

Figure 10.3.Inflation and Inflation Expectations, 1994–2017

(Percent)

Sources: Consensus Economics and Haver.

Note: Last observation: October 2017.

2008 and After: Management of Expectations and Mature Forecasting and Policy Analysis System

Monetary policy became more forward looking and preemptive, with the medium-term forecasts serving as the main basis for discussions of the CNB’s strategy. The endogenous interest rate facilitated transparency and ease of communications. Whether an inflation-targeting central bank chooses to describe its policy path qualitatively or quantitatively, it can tell a coherent economic story in terms of policy reaction to pressures on inflation and output.

Over time, the CNB became comfortable with the decision-making process and more inclined to the view that publishing the complete forecast could be helpful in explaining what the central bank really meant. In the first quarter of 2008, the central bank started publishing the projected interest rate path, with confidence intervals to emphasize that the central bank is never committing to follow a baseline path for the policy rate, but is committed to adjust this path in response to new information.8

Overall Assessment

The Czech Republic has earned a reputation for successful inflation targeting even though actual inflation has often deviated from announced targets and the output gap has often been far from zero. The data show a bias to the downside, with inflation being more often below than above target (Šmídková 2008). According to a quadratic loss function, until 2006 the inflation-targeting error was the costlier facet (Figure 10.4).9 Since then, and especially in the aftermath of the global financial crisis, output gaps have more often been dominant.

Figure 10.4.Loss-Function Values for the Czech Republic, 1998–2015

Source: Czech National Bank.

Undershooting the inflation target in the early years actually bolstered the CNB’s long-term reputation (despite strong criticism at the time), because it helped dispel memories of double-digit inflation before 1998. From the view-point of an endogenous credibility model, the surprisingly low inflation rate at the turn of the century helped convince people that monetary policy had indeed reformed from the previous high-inflation regime to a low-inflation regime.10 After the adoption of the inflation-forecast-targeting framework, strong exogenous macroeconomic shocks again led to significant deviations of inflation from the target and of economic activity from potential.

But the key to maintaining confidence in the system has been that the CNB has consistently and visibly adjusted monetary policy instruments to bring inflation back to target in the medium term (Franta and others 2014; Alichi and others 2015). In its communications, the CNB credibly demonstrated that its actions were indeed in line with its objectives. The forecasting and policy analysis system, with forecasts deriving from a coherent macroeconomic model, helped make explicit the economic rationale: crucial for building the credibility of the Czech inflation-forecast-targeting regime was the capacity to provide a coherent narrative of how interest rates, and the economy in general, might behave over the medium term as inflation was brought back to the announced target.

The CNB’S Forecasting and Policy Analysis System

The CNB’s forecasting and policy analysis system has seen three distinct stages (Figure 10.5). The first was a preliminary phase from 1998 until mid-2002, with an incomplete framework that relied on data-driven, near-term forecasting (that is, the current quarter and the next) models. The second, 2002–08, used the small core model (QPM-gap) to give more emphasis to the medium term and, hence, to the explicit implications of the feedback between monetary policy settings and economic activity and inflation. In a key development, QPM-gap had forward-looking, model-consistent inflation expectations, and an endogenous policy interest rate determined by a policy rule to return inflation to target. The third stage started in mid-2008, when the dynamic stochastic general equilibrium (DSGE) model, QPM-g3, took over.

Figure 10.5.Stages of Czech National Bank Model Development, 1998–2008

Source: Czech National Bank.

The accuracy of four-quarter-ahead inflation forecasts has improved with the more advanced models (Figure 10.6). Moreover, the decline in forecasting errors with QPM-g3 was achieved during the turbulence following the global financial crisis and despite the effective lower bound on interest rates. Negative external demand shocks resulted in overpredictions of inflation, in part because interest rate cuts were blocked by the effective lower bound constraint.

Figure 10.6.Accuracy of Czech National Bank’s Four-Quarter-Ahead Inflation Forecasts

(Percentage point)

Source: Czech National Bank.

Notes: NTF = near-term forecasting; RMSE = root mean squared error.

Early Years: Near-Term Focus

Inadequate forecasting methods, together with the volatile macroeconomic environment and unstable inflation expectations, contributed to large forecast errors in the initial years of inflation targeting (Holub and Hurník 2008; Šmídková 2008). An important part of the sudden and unpredicted disinflation in 1998–99 could be attributed to a sudden fall in global and food prices in that period, that is, to exogenous shocks. However, in addition, near-term forecasting methods underestimated the disinflationary impact of the economic recession. Inflation fell very quickly almost to zero, that is, well below the target and the forecast. Monetary policy came under criticism for being overly tight and for contributing to an unnecessarily deep recession.

Near-term forecasting methods do have a comparative advantage for the short end of the inflation-forecasting horizon. This is true especially for quantifying the near-term impact of cost-push shocks, such as changes in indirect taxes, price deregulation, and global commodity price fluctuations. However, for horizons beyond a couple of quarters the monetary policy feedback cannot be ignored. Following a shock, a credible policy will reestablish the targeted inflation rate over the medium term, with the time profile of adjustment depending on the nature, size, and duration of the source of the shock. Depending on the preferences of policymakers in managing the short-term output-inflation trade-off, inflation may be brought back to target more or less quickly. A proper forecasting framework takes all this into account, with an explicit view of the monetary policy transmission mechanism and the time lags involved.

Next Phase: Model with Medium-Term Horizon

QPM-gap, a small-scale calibrated monetary policy model, was developed over several years, with technical assistance from the IMF (Coats, Laxton, and Rose 2003). The CNB began the process by committing the necessary staff resources: the model development and forecasting team, the team head, the model operators, and the relevant sectoral specialists. Modeling focused on the channels of policy transmission. Initial model calibration was based largely on theoretical considerations and evidence from other small, open economies, but accumulation of domestic data over time allowed modifications to better capture the dynamics of the Czech economy. CNB staff members did extensive tests of model properties to evaluate model-consistent estimates of unobserved variables such as the neutral interest rate and potential output and to identify historical demand- and supply-side shocks. Sectoral specialists were consulted on the magnitudes and timing of model responses to shocks. Forecasting properties were assessed through in-sample simulations and shadow forecasts. Policymakers and staff agreed upon a set of operational rules for an efficient flow of information from the forecasting and policy analysis system to the monetary policy committee (the Bank Board of the CNB). This involved the time frame of the forecast for timely presentation before board decision meetings, personal responsibilities, and clear deadlines at each stage.

The switch to QPM-gap in July 2002 kicked off inflation-forecast targeting in the Czech Republic: the model had the appropriate medium-term focus, it included forward-looking expectations and policy responses, the monetary policy transmission mechanism had an internal channel (through a forward-looking interest rate term structure) and an external channel (through the exchange rate), and, last but not least, it had an endogenous policy interest rate.

Figure 10.7 outlines the structure. The model disaggregates inflation, with separate Phillips curves for core, food, and fuel inflation, and exogenous administered prices. The latter aspect smoothed the transition from the previous near-term forecasting inflation-forecasting method. An aggregate output gap represents the real side of the economy. The team developed tools to decompose the aggregate GDP forecast from QPM-gap into expenditure components, as policymakers wanted to see forecasts for household consumption, government consumption, investment, exports, and imports.

Figure 10.7.Czech National Bank’s QPM-Gap Model: Extended Version from January 2007

Source: Czech National Bank, Inflation Report, I/2007.

The Czech experience bears out that QPM-gap–style models are a good, practical starting point in the early years of inflation targeting. They provide the necessary features to facilitate forward-looking monetary policy discussion. At the same time, they are adaptable to different—and evolving—country circumstances and are not too demanding on human and other resources. In the Czech case, there were three material modifications to QPM-gap during its six years as the core forecasting model.

First, staff members recalibrated the assumptions about long-term equilibrium paths, with an increase in the rate of appreciation of the equilibrium real exchange rate and a reduction in the domestic real equilibrium interest rate. These changes were motivated by forecast errors, in particular by an observed uptrend in the real exchange rate that was not having a visible negative effect on the real economy. The second modification explicitly recognized wage developments as a factor in CPI inflation. The real wage gap was added to the output gap as a component of the real marginal cost gap. This extension of QPM-gap drew on work for the new DSGE model, GPM-g3. Third, staff members reduced the second-round effects of administrative measures and other short-term cost-push shocks in the Phillips curve. This was in line with the observed weakening of pass-through effects and lower inflation persistence—developments that reflected the anchoring of long-term inflation expectations at the target rate.

Advanced Inflation-Forecast Targeting: A DSGE Model

In 2008, the CNB switched to QPM-g3 as its core quarterly projection model.11Table 10.1 provides a comparison between QPM-gap and QPM-g3. The newer model is based on explicit behavioral principles. It preserves stock-flow consistency, whereas QPM-gap defined cyclical gaps from prefiltered trends. Since QPM-g3 disaggregates GDP on national accounts lines, it directly yields forecasts for the major components of spending.12 However, for components of inflation, the modeling and projections team developed satellite models using Kalman-filter methods.

Table 10.1.Comparison of QPM-g3 and QPM-gap
QPM-g3QPM-gap
Explicit derivation using “behavioral principles”Reduced form
Model-consistent expectationsModel-consistent expectations
Stock-flow consistencyFlows only
Basic national accounts disaggregationNo GDP structure
Works with level variablesWorks with “gaps”
Balanced-growth path with technology trendsEquilibrium trends
Simple fiscal blockImplicit treatment
Inflation-forecast-based interest rate reaction functionInflation-forecast-based interest rate reaction function
Carefully chosen “structural shocks”Residuals for each equation
Sources: Andrle and others 2009; and Czech National Bank.
Sources: Andrle and others 2009; and Czech National Bank.

Although the use of DSGE models for forecasting has been questioned (Fukač and Pagan 2006), the forecasting performance for inflation on the monetary policy horizon has improved since 2008. Relatively large errors in the aftermath of the global financial crisis can be attributed to wrong assumptions rather than to a wrong model. The disaggregated nature and the structural form of QPM-g3 have provided ways to incorporate judgment in a consistent way (Brůha and others 2013). At the same time, the forecasting team has been able to develop procedures for using the QPM-g3 model to address the effective lower bound constraint on the policy interest rate (Franta and others 2014).

Near-Term Forecasts in the Forecasting and Policy Analysis System

The forecasting process should allow efficient use of expert judgment. This implies some near-term forecasting input in the baseline forecast. Sectoral experts pay close attention to short-term idiosyncratic factors and may use a variety of models to inform their forecasts, such as single-equation indicator models. Informed judgment easily outperforms model forecasts for current and next-quarter GDP.

Brůha and others (2013) provide several case studies from the CNB’s experience to show how expert information can be usefully incorporated into a structural framework during turbulent times. Even when such adjustments have no effect on the policy outlook, their inclusion may reassure an informed audience that the forecast has not ignored material events. For example, after the global financial crisis, the “cash-for-clunkers” subsidies introduced in western Europe to boost slumping demand for new autos made headlines. They moderated the decline in Czech exports, but at the same time reduced selling pressure on the koruna: the forecast assessment of the overall impact on the Czech inflation rate and interest rate was neutral. It was nevertheless important to incorporate the subsidies explicitly into the forecast, because otherwise the CNB board and outsiders might have thought that the forecast story had forgotten something obvious.

A managerial issue is to make sure that the modeling team and sectoral experts cooperate effectively. At the CNB, before 2004, the near-term forecasting team and the modeling and projections team were in separate divisions (Real Economy Division and Economic Modeling Division) (Figure 10.8). This created tension during integration of near- and medium-term forecasts. In 2003, board members expressed dissatisfaction with the forecasting process.13

Figure 10.8.Evolution of the Organizational Structure at the Czech National Bank

Source: Czech National Bank.

A restructuring in 2004 merged the two teams into a single Macroeconomic Forecasting Division (Figure 10.8). A division director became responsible for managing the whole forecast process and for making sure that both groups make cooperative input into the final forecast. A department-wide forecasting team of about 10 people now ensures that the other divisions of the department are actively involved in forecasting. All divisions send experts to the team, which reports to the management of the department and presents its work at several departmental meetings during each forecasting round. The team head, chosen from the core model operators, presents the forecast at meetings with the board.

Since 2004, CNB macroeconomic forecasts have used near-term forecasting estimates only for the most recent quarter (nowcasts) and for one quarter ahead. The team also prepares forecasts for regulated prices, indirect tax changes, and government consumption, which are exogenous inputs into the general-equilibrium core model over the whole forecast horizon. Similar treatment applies to the foreign economic outlook (from the External Economic Analyses Division), and to fiscal impulse estimates (from the Monetary Policy and Fiscal Analyses Division).

Reckoning for Uncertainty

Decision-making is trickiest amid high uncertainty—for example, during the global financial crisis, the European sovereign debt crisis, and following the first encounter with the effective lower bound. In such situations, the central bank’s board may request alternative scenarios and sensitivity analyses to see how different assumptions would change the outlook. A model-based forecasting system greatly facilitates this process. In contrast, to produce even one such scenario under a pure near-term forecasting system would require time-consuming iterations and negotiations among sectoral specialists. Policymakers have found the capacity for systematic examination of alternative feasible outcomes reassuring (Tůma 2010).14 Forecasting tools that help policymakers promptly, at the very time they are weighing risks of alternative actions, have special value (Hampl 2014).

The Human Resource Input

An effective forecasting and policy analysis system team does not have to be large, but it does need a balance of complementary skills. CNB experience suggests that the process can begin with a relatively small team and can be strengthened over time. Specialized modeling skills are not acquired quickly, either through training of existing staff or through recruitment. In both cases, it is more important to have a good match between job requirements and individual skills than to fill open positions without delay. This said, narrow specialization is unhelpful, either from the cooperative viewpoint of team output or from the individual viewpoint of the careers of team members. Diversification of skills can be achieved over time through encouraging staff members to take an interest in the broader aspects of the work of the team and through timely job rotation—policies that are at the same time likely to improve the work environment and the quality of output.

In 1998, most economists in the CNB’s Monetary Department worked as sectoral specialists, focusing on analyses of the real economy, monetary developments, and the balance of payments. The department’s output was largely descriptive and statistically oriented material. Forecasting was based on judgment and simple near-term methods. There was a widespread belief within the CNB staff at the time, reflected in the models in use, that the short-term interest rate had a negligible effect on aggregate demand. Monetary policy modeling at the central bank involved few economists. When policy was mainly directed at maintaining the exchange rate peg, this lack of a core macroeconomic framework was of little importance.

In the 1990s the supply of well-qualified Czech macroeconomics graduates was very limited, but the Czech education system did provide high-quality training in mathematics and other technical subjects. The few economists at the CNB that did focus on modern macroeconomic analysis produced work of high technical quality. Moreover, by the turn of the century, graduates well-schooled in modern macroeconomics were emerging from the universities, and the CNB became a successful recruiter.

Purely technical knowledge, however, is insufficient—all forecasting and policy analysis system staff should have at least some acquaintance with modern, open-economy, macroeconomic theory, and the leadership should be experts in the field. Economists with a talent for synthesizing various strands of thought, and with drafting skills, can shape the central bank’s economic story of a forecast into an intelligible narrative, without losing the technical insights. (The right amount of technical detail depends on the audience—for example, policymakers or academics would demand more than journalists or the general public.)

CNB senior management has continued to support the forecasting and policy analysis system. By acknowledging that its input made a difference to their decisions, policymakers have boosted morale and created a strong incentive for staff members to remain with the team and perform well. Moreover, the opportunity to acquire valuable know-how and to add to individual human capital is also a motivating factor.

Forecasting at a central bank involves an intensive schedule of meetings and rigid deadlines. Solutions must be found for unexpected economic or technical problems.15 Compromises must be struck between differing staff views on various issues. Presentations for policymakers have to be prepared on short timelines. And at least once a quarter, forecast error evaluations should be made.16 The nature of the work puts pressure on the forecasting team and can result in significant stress.17

The CNB allows forecast team members the opportunity to take breaks to work on other projects with less stressful deadlines and longer planning horizons (for example, model development, near-term forecast work, training, or even secondments to some other central bank or research institution). At the CNB, economists regularly switch between forecasting and research. Ideally, the selected research projects focus on some aspect of model development, for example, extensions with new blocks.18

Experience at the CNB (and also at other central banks) suggests that research by forecasting and policy analysis system members is more fruitful than external research for core model improvements—in part because the costs of knowledge transfer are so much less. On the other hand, research projects should not be vetted narrowly. It is never clear where the next good idea is going to come from.

Even an appreciative working environment and a system of job rotation that allows staff members time to pursue—and publish—other research interests cannot ensure that crucial staff members are retained. In principle, the economics staff should be sufficiently flexible that, between forecasts, the entire forecasting and policy analysis system team could be switched for another—with outgoing members taking over the functions of the incoming. Not that such a switch would ever be a good idea in practice, but the potential to do it defines an ideal standard for adequate backup.

To the same end, models and data sets should be fully documented and stored such that they are accessible to the whole team and not just to individuals who might leave at some point.

Ownership of the Forecast

Ownership of the forecast—who decides the guiding assumptions and judgments—reflects the management structure of the central bank, the nature of its monetary policy decision-making, the extent to which policymakers shape the assumptions, and existing requirements for accountability. Since these differ in important ways across countries, one cannot speak about universal best practices.

The main forecast considered for policy decisions can be labeled interchangeably as a board (or monetary policy committee) forecast, a staff forecast, or a central bank forecast.19 There is no hard and fast delineation among these labels. They are all central bank forecasts, in that the institution is ultimately responsible for their production—it provides the resources, it publishes results, and it acknowledges their influence on policy decisions. Under any arrangement, one assumes that the central bank would always in the event of criticism defend the integrity of the forecasting process and the quality of the underlying research. At the same time, nobody would expect it to defend any particular aspect of any given projection.

The CNB Inflation Report describes forecast ownership in the following way:

The forecast is the key, but not the only, input to our monetary policy decision-making. Unless the economic situation requires an extraordinary monetary policy meeting, the Bank Board meets eight times a year to discuss monetary policy issues. At four of the meetings (in February, May, August and November) we discuss a new forecast, while at the other four (in March, June, September and December) we discuss the risks and uncertainties of the most recent forecast in the light of newly available information on domestic and foreign economic developments. Due to the arrival of new information since the forecast was drawn up and to the possibility of the Bank Board members assessing its risks differently, the decision we adopt may not fully correspond to the message of the forecast prepared by our experts. (CNB Inflation Report, IV/2017)

The substantive difference between the CNB forecast and an official central bank forecast lies in the degree to which the forecast is the basis for actual policy. If the forecast by design reflects the view of policymakers, it is official, and the key aspects are theirs to defend. Operationally, an official forecast would apply when board or monetary policy committee members, or the central bank governor, are heavily involved in forecasting (for example, the Reserve Bank of New Zealand). Given their involvement, policymakers have little room to deviate from the official forecast: they are accountable for it.

Board responsibility for the shape of a forecast would not be feasible at the CNB. The board is not just a monetary policy decision-making body. It also oversees the management of the central bank as an institution, a function that involves a wide range of highly technical, sensitive, and time-consuming responsibilities, including the supervision of the whole Czech financial system. This limits the time that individual board members can devote to monetary policy. Time-tracking software used by the vice-governor overseeing the Monetary Department showed that he devoted only 10 percent of his time to monetary policy (Hampl 2014). Staff members meet with the board only twice during each forecasting exercise—once focused on assumptions and initial conditions and the other meeting on alternative and sensitivity scenarios. In effect, decision-making, and the communication strategy of board members, may be quite individualistic, as frequently surfaces in split votes.20 On occasion, the board as a whole may differ from the staff forecast.

The question of ownership is related to issues of communications and transparency. When monetary policy decisions are made by votes in a committee—as opposed to consensus or by the governor—each member may be basing their vote on an independent, informal, forecast. The staff forecast, however, is likely to be the only fully coherent macroeconomic projection. It is also likely to be the point of departure for the various member outlooks and the basis of reference for policy discussions. So, it has intrinsic interest from the viewpoint of public accountability, even if it is not necessarily the overriding factor in a committee vote.

The fact that board members may express reservations may have eased the decision of the CNB to go for full disclosure. The central banks of Israel, Norway, Sweden, and the United States, which also maintain highly transparent communications, also make decisions by committee vote. This has not, however, been an overriding factor: in New Zealand, the Reserve Bank of New Zealand has full disclosure, yet the governor alone is accountable for policy actions and is engaged in the forecast process.

Communications and Transparency

Early Awkwardness

At the outset of inflation targeting, when the CNB relied on near-term forecasting methods, interest rates (as well as the exchange rate) were assumed to be constant over the forecast horizon. There was no need to think about publication of the interest rate path. But such a forecast ignored the nominal anchor responsibility of monetary policy, and was thus not internally consistent (Skořepa and Kotlán 2006). Nor was it easily comparable to forecasts of financial market analysts and other institutions, which incorporated their best guess about future monetary policy. The forecast did not provide quantified guidance on the likely direction and speed of actions required to achieve policy objectives. And when the policy rate was changed, in a direction consistent with the inflation pressures in the most recent forecast, the CNB faced questions on whether this forecast was now still valid, and if not, what an updated forecast would look like. These were hard to answer with any clarity given the lack of well-defined monetary policy transmission in the existing CNB forecasting models.

Increasing Transparency with the Forecasting and Policy Analysis System

Following the introduction of QPM-gap and a properly structured forecasting and policy analysis system, in 2002, the forecast did include an endogenous interest rate path (for the three-month Prague interbank offered rate [PRIBOR]). Press conferences and inflation reports for some years gave only a qualitative description of the path.

This was, and still is, the most common approach. For example, Mishkin (2004) states the following:

Although economists understand that any policy path projected by the central bank is inherently conditional because changes in the state of the economy will require a change in the policy path, the public is far less likely to understand this. When new information comes in and the central bank changes the policy-rate from its projected path, the public may see this as a reneging on its announced policy or an indication that the central bank’s previous policy settings were a mistake.

However, the risk-of-confusion argument became less convincing in view of the combined experiences of inflation-forecast-targeting central banks, and their capacity to underline the conditionality of the projection through the presentation of confidence bands around the baseline path, and alternative scenarios.

Clear Language and Explanation

Modelers and forecasters do not necessarily write well. At the CNB, the managers of the Monetary Department, who typically are economists with good communications skills, play an important role in editing the final versions of the reports, using their experience with communications to the board to strike the right balance between technical rigor and digestibility.

Model changes require careful explanation to policymakers. When QPM-g3 replaced QPM-gap, some concepts familiar to the board members disappeared, replaced with new ones. For example, QPM-g3 replaced the output gap with endogenous real marginal costs of producing consumer goods and with firms’ markups. The change was difficult for board members to digest.21 Several rounds of nontechnical presentations of the new model to the board members were needed to facilitate the transition. Since then, staff give regular presentations to new board members on the forecast process and materials.

Toward Full Disclosure

While the qualitative description of the interest rate forecast generally helped move the term structure of rates in the desired direction, opinion in the board shifted toward explicit disclosure. In early 2008, the CNB decided to publish the forecast path for the three-month PRIBOR, in a fan chart with confidence bands based on past forecast errors.22 This step was taken to enhance the transparency of the CNB forecast and the associated monetary policy decisions, and to increase the effectiveness of monetary policy transmission. At the same time, the confidence bands illustrated the degree of uncertainty, and the conditional nature, of the published path.

Over time the CNB has broadened, deepened, and quickened its communications on policy actions. The board issues a press release immediately after the decision is taken, and the Governor gives a press conference the same afternoon. The monetary policy decision is explained either in the context of a new macro-economic forecast (four times a year), or, for interforecast policy meetings, of a risk assessment to the previous quarterly forecast (also four times a year since 2008).23 The presentations give the votes cast by the board members on interest rate decisions. Since 2014, the governor has provided a written explanation of the decision, followed by a question and answer session. Eight days after the policy meeting, the CNB publishes the minutes (with the individual votes since 2008), and the Inflation Report, which has full details of the forecast. Over time, the structure of the Inflation Report has evolved to put more emphasis on the forward-looking content and to deliver a more concise message.

Another regular means of communication is a schedule of quarterly meetings with financial market analysts (both local and foreign), at which senior staff present the new macroeconomic forecast, followed by a discussion with one or two board members. These meetings take place one day after the policy decision announcement, along with the release of the Executive Summary of the Inflation Report, which includes a detailed forecast table.24

In all, outside observers see the CNB as in the avant-garde of transparency in the conduct of monetary policy. Dincer and Eichengreen (2014) calculate an index of central bank transparency based on five broad criteria (political, economic, procedural, policy, and operational), each of which has three subcategories. The index for 2014 places the CNB as the second-most transparent central bank in the sample of more than 100, with a score of 14.5 out of a maximum 15.

Has the CNB gone too far? Former Governor Tůma (2010), after his departure, expressed doubts about the net benefits of publishing board votes by name: “[O]n the margin, publishing of individual votes goes too far and may actually be detrimental to good policy ... the greater transparency may lead to a more opportunistic behavior of the chairman and less frequent swing votes by the Board members.” On the other hand, in 2013 some board members felt discomfort when the board decided not to publish the individual votes and to restrict communication of individual opinions on the exchange rate. This was intended as a special measure to avoid any confusion among the public that differing individual voices within the board might create (Franta and others 2014).

Managing Expectations—The Exchange Rate Instrument Experience25

By 2010, the Czech economy seemed to be recovering from the postcrisis recession. But in late 2011, the marked slowdown in the euro area and continuing domestic fiscal consolidation began to put a damper on growth. By the second half of 2012, inflation was below the 2 percent target and output was below potential. As the CNB inflation forecast signaled further undershooting of the target, the central bank cut policy rates to the effective lower bound in November 2012. Yet the projections suggested that a further easing in monetary conditions was necessary. The central bank needed a new policy instrument to provide the monetary ease needed to reach the inflation target.

Svensson (2001) advocates that exchange rate management be a complementary monetary policy tool to escape the effective lower bound problem. CNB analysis concluded that weakening the nominal exchange rate would indeed be an effective strategy against a cyclical slowdown (Franta and others 2014). The modeling and projections team adapted QPM-g3 to derive model-consistent scenarios in which the exchange rate is effectively an additional instrument. Model simulations reported in Figure 10.9, which roughly replicate real-time results available in 2013, show the effects of a fully anticipated 5 percent weakening of the exchange rate for various projected durations at the effective lower bound. The combined effect of these interest rate and exchange rate channels—which depend entirely on expectations—produces a significant increase over the medium term in real GDP growth and inflation. Since 24 percent of the CPI basket is directly imported, and another 9 percentage points is imported as intermediate inputs, the strong impact is not surprising.

Figure 10.9.QPM-g3 Model Impulse Responses to a Fully Anticipated 5 Percent Weakening of the Exchange Rate for Different Lengths of Stay at the Effective Lower Bound

Source: Czech National Bank.

Note: CPI = consumer price index; PRIBOR = Prague interbank offered rate.

Implementation of such a strategy would require managing expectations because the exchange rate, unlike the policy interest rate, is not under the direct control of the central bank. To further complicate matters, the high degree of capital mobility imposes a link between expected short-term interest rates in the Czech Republic and the exchange value of the koruna. For example, the longer the expected interest rate stays at the floor, the greater the depreciation of the exchange rate. Macro models embody this link in an uncovered interest parity condition, modified to allow a time-varying risk premium.

In autumn 2013, the CNB announced that it would add the exchange rate as an additional tool for easing monetary conditions within the context of the inflation-forecast-targeting framework: “The CNB will intervene on the foreign exchange market to weaken the koruna so that the exchange rate of the koruna against the euro is close to CZK27.”26

Ideally, the strategy would increase short- to medium-term inflation expectations without deanchoring long-term expectations. For this purpose, the exchange rate must be perceived as a temporary tool, not an additional longer-term objective, so that the public believes that the central bank remains committed to its longer-term 2 percent inflation target. The CNB therefore underlined to the public that the exchange rate policy was subject to revision as conditions changed. The communications worked. Long-term expectations of inflation held firm at the target rate (Table 10.2).

Table 10.2.Czech Republic: Inflation Expectations(Annual percent)
201420152016Long-Term Target
Sep. 2013 Survey1.61.82.02.0
Apr. 2014 Survey1.22.22.02.0
Change (percentage point)−0.40.40.00.0
Source: Consensus Economics.
Source: Consensus Economics.

In the exchange market, financial market participants understood that the CNB was using the exchange rate tool only temporarily to boost economic activity and to avoid the risk of deflation. They realized too that the CNB had unlimited intervention power to buy foreign currency since it could supply koruna indefinitely. The credibility of the policy was such that to achieve the desired depreciation the CNB bought foreign exchange over just two days. The koruna then traded at or above 27 per euro for three years, without any further CNB intervention.

During this period, growth picked up, and the output gap closed. Industrial production growth moved from a low of just over 3 percent in September 2013 to over 5 percent by August 2014, reflecting in part the effect of depreciation on exports. Inflation remained somewhat lower than expected, partly because of administered prices, some of which declined. The exchange rate depreciation nevertheless played an important role in the Czech Republic’s averting the strong disinflationary tendencies evident elsewhere in the European Union.

One should be careful about generalizing from the Czech experience with exchange rate policy. Its apparent success depended to a large extent on the strong credibility of the inflation-targeting program that has been built over a period of many years. And the CNB has cultivated streamlined links to the communications media, which allowed it to get out effectively to the public the nuances and conditions of the policy. Not all central banks possess these advantages. Furthermore, the Czech Republic is a small economy: its deliberate exchange rate depreciation did not create the same concerns about a beggar-thy-neighbor policy, and about retaliation, that would arise if a large economy employed the same strategy.

Conclusions

This chapter describes the development and practice of inflation-forecast targeting in the Czech Republic since the turn of the century. A remarkable feature of the history is that over the course of a decade, Czech monetary policy went from a primitive condition, in a country with very limited experience with the functioning of a modern market economy, to the state of the art.

The record of the CNB for controlling inflation under the inflation-forecast-targeting regime stands up well in any international comparison. Expectations for long-term inflation in the Czech Republic have been firmly anchored at the target rate of 2 percent. It is not too important that actual year-over-year inflation has often been significantly off target. The key to keeping public confidence has been that, in the event of any deviation from target, the central bank—consistently and visibly—has acted to return inflation to target over the medium term.

Underlying the transformation of policy conduct within the central bank was a commitment to establishing and maintaining a forecasting and policy analysis system adequate for the implementation of inflation-forecast targeting. This has required an ongoing investment in human capital, the development of up-to-date models for forecasting and policy analysis, institutional reorganizations to allow efficient provision of relevant economic intelligence to inform policy decisions, and improvements in the dialogue between economists and policymakers to ensure that they were working from mutually comprehensible assumptions. One of the benefits of model-based forecasting has been that the CNB can explain its policy actions with a transparent, coherent, economic narrative. This has enabled a bold opening of external communications, with complete disclosure of the central bank’s economic forecast. Outside assessments of central bank transparency have placed the CNB near the top of the international ranking.

Within the Czech Republic, there is much more awareness today than at the start of the century about monetary policy issues. Media coverage has become better informed. More important for the long term has been the growth of interest in monetary policy at the universities and the emergence of a generation of highly qualified, policy-oriented monetary theorists and model builders. This has given the central bank and other institutions a deep pool of talent. The ability to recruit and maintain in-house human capital, of sufficient size and flexibility to cope with turnover, is crucial for the sustainability of an effective forecasting and policy analysis system.

Internationally, the CNB has become a recognized leader for the formulation and conduct of monetary policy. Despite its relatively small size, the Czech central bank has become an important contributor of technical assistance. Model builders from the CNB have had a major influence on the models used for inflation targeting at numerous central banks.

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3

Money growth rules as a nominal anchor were completely discredited. Financial innovation, and resulting instability of the demand for money (on any definition), had led to the failure of numerous attempts at money growth rules in many countries. Their prospects were, if anything, worse in the Czech Republic, in view of the rapid, even hectic, changes taking place in the financial system.

4

The unemployment rate peaked at 9.3 percent in 2000. More detailed discussions of the history of monetary policy in the Czech Republic are in Laxton, Rose, and Scott (2009) and Ötker-Robe and Vavra (2007).

5

Laxton, Rose, and Scott (2009) give a thorough description of how to set up a forecasting and policy analysis system for inflation-forecast targeting.

6

For complete documentation of the forecasting and policy analysis system introduced in 2002 see Coats, Laxton, and Rose (2003).

7

In realistic models of economies with important lags in the monetary transmission mechanism it simply is neither feasible nor optimal to keep current inflation on target at all times.

8

The CNB currently develops its confidence bands based on an analysis of past forecasting performance, but it is now technically possible to construct confidence intervals for nonlinear models. Relevant nonlinearities include the Phillips curve and the floor on nominal interest rates. See Clinton and others (2010).

9

The loss function assigns a weight of 1, 1, and 0.5 on the squared deviation of inflation from its target, the output gap, and change in the policy rate, respectively. In practice, changes in the policy rate make empirically negligible contributions to the loss.

10

Alichi and others (2009) present a model in which people are initially undecided as to whether monetary policy will adhere to a new announced low-inflation target or revert to a previous policy of high inflation. In their expectations of future inflation, some weight attaches both to the new target and to the old high rate. Over time, the central bank builds credibility by keeping inflation low: the weight on the announced target goes to one, while that on the old high rate goes to zero.

11

The CNB was introduced to DSGE models by IMF technical assistance. However, CNB modelers developed QPM-g3 from scratch. It was the first DSGE model to be used as a core quarterly projection model in an inflation-forecast-targeting central bank.

13

For example, very critical remarks can be found in the transcript for the October 30, 2003, board meeting (Czech only): http://www.cnb.cz/miranda2/export/sites/www.cnb.cz/cs/menova_politika/br_zapisy_z_jednani/2003/2003_10_30/pt_10_SZ_30_10_03.pdf.

14

Tůma (2010): “The forecasting system must give the policymakers the comfort in making these ex ante decisions under uncertainty. This implies that forecasting accuracy is not as important as the ability to consistently differentiate between various alternative future developments. Our forecasting system has developed over the years to a truly disciplining tool for the policy debates and a platform for analyzing risks and their policy implications. These properties made it an acceptable tool for the policymakers.”

15

Time pressure on staff, as well as the risk of errors, can be reduced by investing in automated data management, production of charts, tables and presentations, and so on.

16

Each quarter, CNB staff do a forecast evaluation based on a detailed model-consistent analysis of the factors contributing to forecast errors. The results of these evaluations are presented to the policymakers. They help identify priority areas for model improvement.

17

The modeling and projections team has grown to six economists. The enlargement of the team made it possible to create a rotational system composed of two three-member teams, which rotate every year between forecasting and model development. During each calendar year, one of the three-member teams is responsible for the forecast and the other does model development and economic research to support the forecasting and policy analysis system.

18

During the initial period of the global financial crisis, policymakers were concerned with the role of financial frictions in the transmission mechanism. To test the forecasting model for the presence (and size) of shocks originated from the financial sector, the model was extended to include a financial block. This work was carried out by those members of the forecast team who were not responsible for forecasting at the time.

19

Policymakers may have forecasts of their own. For example, the Federal Open Market Committee of the Federal Reserve publishes summaries of the economic projections of members.

21

Hampl 2014, slide 23.

22

This decision was announced on March 8, 2007.

23

Between 2009 and mid-2013, the CNB published a fan chart for the endogenous CZK/EUR exchange rate at the press conference—a practice that was suspended between November 2013 and January 2018, when the CNB used an exchange rate floor as an unconventional monetary policy instrument.

24

The board publishes a full transcript of policy meetings with a delay of six years. The six-year lag was chosen to match the term in office of individual board members to avoid inhibiting frank and open debate. This publication has yet to attract much attention from academics or journalists.

25

For more on the CNB’s experience of adding the exchange rate as a complementary monetary policy tool to stimulate the economy when the policy rate is at the effective lower bound, see Alichi and others (2015), Clinton and others (2017), and Franta and others (2014).

26

In a subsequent question and answer session, the CNB clarified that the intervention is one sided: “What does the CNB’s exchange rate commitment mean for the future evolution of the koruna exchange rate? This means the CNB has undertaken to prevent excessive appreciation of the koruna below CZK27/EUR. On the stronger side of the CZK27/EUR level, the CNB is preventing the koruna from appreciating further by intervening on the foreign exchange market, that is, by selling koruna and buying euro. On the weaker side of the CZK27/EUR level, the CNB is allowing the koruna exchange rate to float. In other words, the exchange rate will be close to CZK27 to the euro or even weaker in the period ahead. Potential fluctuations to levels weaker than CZK27/EUR will be determined by supply and demand on the interbank foreign exchange market.”

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