Report

Nikhil Vellodi, Bank of Papua New Guinea PFTAC Workshop, Apia, Samoa, 15th-23rd November, 2011, “Improving Analytical Tools for Better Understanding” Introduction Part I: Theory ◦ Model Description. ◦ Solving and Estimating the Model. Part II: Application to PNG ◦ The PNG Database. ◦ Impulse Response Functions and Historical Decompositions. ◦ Drawbacks, Things to Work on. Conclusion 2 What is an FPAS model? How and where are they used? How do they relate to the current workshop objectives? Introduction 3 Small macroeconomic model. Built at the IMF: Berg, Karam and Laxton, 2006, “A Practical Model-Based Approach to Monetary Policy Analysis: A How-To Guide”, IMF Working Paper 06/81. Similar to many workhorse models used at central banks. Mainly differs in the estimation technique. Blends New Keynesian theory with DSGE modeling. ◦ No explicit microfoundations, as in a DSGE model. ◦ Uses IS/LM approach to aggregate demand and supply Price stickiness in the short-run and demand equation/price setting equation. ◦ Demand and price-setting equations taken from New Keynesian Theory. Phillips Curve and Output Gap equations broadly derived from Calvo (1982) price setting rules. Introduction 4 Used for forecasting and monetary policy analysis. Mainly short-medium term forecasting. Both qualitative and quantitative analysis. ◦ Calibration and estimation, using actual data, rather than pure calibration as for DSGE or CGE models. Explicitly models the monetary transmission mechanism. Mainly used in central banks and other financial economic institutions. Introduction 5 Provide thorough yet concise analysis of current macroeconomic conditions, and implications for policy going forward. Draw together key macroeconomic variables, such as the monetary and fiscal policy stances, the real exchange rate, the output gap, inflation and the real interest rate, all of which will be discussed in detail over the course of the workshop. Introduction 6 The Model Description for PNG. Solving the model. Estimating the model. Part I: Theory 7 Overview of Model Structure ◦ Global economy split into Home and Rest of World. External conditions are a major determinant of domestic conditions, especially for small, open economies. ◦ Six main equations govern each region: Aggregate Demand equation (Output Gap equation). Price-setting equation (Phillips Curve). Exchange Rate equation (Uncovered Interest Parity condition). Monetary policy reaction function (Taylor Rule). Fiscal policy reaction function (Fiscal Balance equation). Non-mineral revenue equation. Part I: Theory: The Model Description 8 The Output Gap equation describes the determinants of aggregate demand. Output is determined by past and future output, as well as the real interest rate, the real exchange rate, real commodity prices, the non-mineral fiscal balance and world output. Part I: Theory: The Model Description 9 The Phillips Curve describes the trade-off between prices and output. An increase in the output gap implies a build-up of demand pressures, which lead to inflation. Core inflation is determined by past and future core inflation, the past output gap and lagged headline inflation. Part I: Theory: The Model Description 10 The Interest Parity Condition links the real exchange rate with the real interest rate. An increase in the domestic real interest rate, ceteris paribus, leads to capital inflows, and hence an appreciation of the real exchange rate. The real exchange rate is determined by the future real exchange rate, the difference between domestic and world interest rates and the domestic risk premium on investment. Part I: Theory: The Model Description 11 The Taylor Rule describes the manner in which monetary policy is conducted. In response to an increase in inflation, the central bank raises the nominal interest rate, in order to reduce demand and hence inflation. The nominal interest rate is determined by the past rate, the real interest rate, core inflation, future deviations of core inflation from trend and the output gap. Part I: Theory: The Model Description 12 The fiscal balance equation describes what determines the profile of government spending and saving. An increase in the output gap correlates with increased government revenue, increases in commodity prices increases revenue through export receipts and dividend payments. The fiscal balance is determined by the past balance, past output and past commodity prices. Part I: Theory: The Model Description 13 The non-mineral revenue equation was inserted to allow a richer description of the role of non-mineral revenue in the model. By separating the fiscal balance into both revenue and price effects, we can directly shock the revenue term, rather than just the commodity price term. Part I: Theory: The Model Description 14 Simply links core and headline inflation. Part I: Theory: The Model Description 15 In a couple of stages… 1. Find the “steady-state” solution. Variables have settled on constant values in time. To find SS, drop the t subscripts, since values same from one period to next. e.g. yt, yt+1, yt-1 all become y. Not unique. Many SS solutions may exist. 2. Determine dynamic properties. “Two-point boundary” technique. Pick two SS solutions. Then the dynamic solution is the path traced by the variables in getting from one to the other. Impulse response functions similar technique. Start at one SS solution, perturb one shock variables, and see how the model returns to equilibrium (may be same or different from starting point). Part I: Theory: Solving the Model 16 Bayesian Estimation Techniques. ◦ Simply application of Bayes’ Rule: ◦ Start with a prior assumption on parameter distributions, before data is analysed (Pr(M). ◦ Use likelihood function (Pr(D|M) )/Pr(D)) to generate posterior (Pr(M|D)). This is the impact of the data on the choice of the model. ◦ Modeling rationale for using Bayesian estimation. Formation of priors goes hand-in-hand with economic understanding. Choosing the initial values for the parameters requires an intuition for their role in the economy. Part I: Theory: Estimating the Model 17 The PNG Database. Impulse Response Functions. Historical Decompositions. Drawbacks of FPAS model. Things to Work on. 18 Non-mineral real GDP output gap (HP, 1600) 5.0 4.0 3.0 2.0 1.0 0.0 -1.0 -2.0 -3.0 The PNG Database 19 Output Gap and Core Inflation (Y-o-Y, Annual Rate, Right Axis) 5.0 25 4.0 20 3.0 15 2.0 1.0 10 0.0 5 -1.0 0 -2.0 -3.0 -5 Core CPI, Change y-o-y annual rate The PNG Database 20 Mineral Revenue in % non-mineral GDP 25.00 20.00 15.00 10.00 5.00 0.00 The PNG Database 21 Deviation of Non-Mineral Deficit from MTFS Target in % of Non-mineral GDP (+ Fiscal Expansion) 8.00 6.00 4.00 2.00 0.00 -2.00 -4.00 -6.00 -8.00 -10.00 Deviation of nonmineral revenues from long-run trend in % of nonmin GDP (+ expansionary fiscal policy/revenue shortfall relative to trend) Deviation of fiscal expenditures from MTSF norm in % of nonmin GDP Deviation of nonmineral fiscal deficit from MTFS target in % of nonmin GDP (+ expansionary fiscal policy) The PNG Database 22 Nominal and Real Interest Rates (commercial lending rates, weighted average total advances) 25 20 Commercial lending rates (weighted Average Total Advances) Real lending rate (core, y-o-y) 15 10 5 0 -5 -10 The PNG Database 23 Deviation of Real Effective Exchange Rate from Trend in % (+ Depreciation) 15 10 5 0 -5 -10 -15 -20 The PNG Database 24 Commodity Price Index (in US$ and in DC, real terms) 250 200 150 100 50 0 Commodity Price Index, 2005 = 100, includes both Fuel and Non-Fuel Price Indices Real Commodity Price Index (Index expressed in Kina, divided by PNG Headline CPI), 2005=100 The PNG Database 25 Selected charts. ◦ Shocks to domestic demand and non-mineral . ◦ Charts generated from prior distributions. Not using the posterior distributions generated via estimation. Impulse Response Functions 26 Impulse Response Functions 27 Impulse Response Functions 28 For a given equation, demonstrates the relate explanatory power of each variable throughout the sample period. E.g. for the output gap, gives a reasonably clear and thorough impression of what the model thinks is driving demand conditions in the PNG economy. 29 30 The Chart tells a compelling story of PNG’s macroeconomic history over the last decade… ◦ The global financial crisis clearly hit demand, through an appreciation in the real exchange rate and external demand conditions, but a fiscal spending stimulus compensated, keeping the output gap almost at zero. ◦ In the years leading to that, there had been a period of fiscal tightening, which had a negative effect on demand. ◦ The real interest rate goes through periods of being more or less significant. E.g. there was a large decline in real lending rates around the crisis (2008), which had a stimulating effect on demand. 31 What it doesn’t talk about. ◦ Aggregate supply, current account. These are captured indirectly through the other endogenous variables. Modeling changes in supply through potential output is difficult. Too computational intensive, couldn’t estimate the model. May require more explicit microfoundations, with sectors, etc. Technical requirements ◦ Have to leave model estimation running overnight! Sensitivity to priors 32 Elaborating the inflation process ◦ May split inflation into imported and domestic. There have been secular shifts in the causes of inflation over the last decade. Refining the transmission mechanism. ◦ Spread between commercial lending rates and OMO rates large and erratic. Employing one interest rate to act as both the Bank signaling rate and the domestic demand determining rate may be infeasible. Could use two separate rates, and add an equation linking the two. Revisiting the sample period. ◦ Was there a trend break in fiscal policy in the early 2000s? 33 How does the FPAS fit in with PNG and the other South Pacific Islands? ◦ Compliments larger DSGE model, both in terms of time-frame and explanatory power. DSGE model has sectoral elaboration, models supply side in greater depth. Operates over the medium-long term. Qualitative analysis only. Calibration only, no data or estimation involved. ◦ Just building the model is useful in itself. Compiling the database puts the user in touch with key data series. Calibrating priors forces user to think about how key variables interact. ◦ Point towards which all of the current work is leading. 34 THANK YOU! 35