kosticky Tools for Monetary Policy with DSGE Models g3 – case studies Jaromír Tonner Brno, autumn, 2011 OPVK_MU kosticky •‹#› •2 Outline •Expert judgments •Case studies •Sensitivity analysis kosticky •‹#› •3 Expert judgments •Measurement errors •Seasonal adjustment •Expert judgments on filter •Expert judgment on forecast • kosticky •‹#› •4 Measurement errors •ME reflect our priors concerning data reliability. •ME brings some problems in distinguishing between structural shock and measurement error. •Even in case of ME, a significant portion of information can be used by the model. •Another problem is that filtered vars need not match exactly raw data, so then ... •...we investigate factors for that discrepancy...what are models or data deficiencies. kosticky •‹#› •5 Measurement errors kosticky •‹#› •6 Seasonal adjustment kosticky •‹#› •7 Expert judgment on filter kosticky •‹#› •8 Expert judgment on forecast •All forecasts are judgemental forecast (calibration of the model, filtering setup, trajectories of structural shocks), but •we may impose judgements on the development of a particular variable by endogenizing structural shocks innovations, but.... •the question is... what shock or set of shocks to choose and whether these shocks should be treated as anticipated or unanticipated...in which periods •A special case represents explaining of a current development of a given variable by future innovations...these must be treated as anticipated by all agents in the economy... •A solution is not unique, we can choose the set of shocks that is the most likely... kosticky •‹#› •9 Case studies outline •Nominal wages •Increase of credit premium •Foreign trade fall and openness •Car scrapping subsidies •After-crisis steady states growth rates kosticky •‹#› •10 Case studies of nominal wages •Real variables slump, nominal wages sticky •It implies inflation pressures •Model in reduced form •Find reason •Expert judgment kosticky •‹#› •11 Case studies of nominal wages kosticky •‹#› •12 Case studies of nominal wages • •Median of gross month salary (Kč/month) • • •1. half of 2008 •1. half of 2009 • •Employees •22 064 •21 837 • •Fired •18 478 • • •New • •18 115 • •Firms •21 330 •21 309 • •Firms could keep the same wages only if fired were • employees with low salary and... •Source: prezentation Spáčil, Kasal: Projevy krize v datech ISPV, www.trexima.cz kosticky •‹#› •13 Case studies of nominal wages • •Number of employees (thousands) • • •1. half of 2008 •1. half of 2009 • •Employees •1 383 •1 409 • •Fired •323 • • •New • •210 • •Firms •1 707 •1 619 • •1/3 less new employees than fired •Source: prezentation Spáčil, Kasal: Projevy krize v datech ISPV, www.trexima.cz kosticky •‹#› •14 Case studies of nominal wages • •Hours worked monthly • • •1. half of 2008 •1. half of 2009 • •Employees •154.8 •149.3 • •Fired •148.6 • • •New • •154.1 • •Firms •153.6 •149.9 • •Fired have the lowest hours worked •Source: prezentation Spáčil, Kasal: Projevy krize v datech ISPV, www.trexima.cz kosticky •‹#› •15 Case studies of nominal wages • •Hours of sickness monthly • • •1. half of 2008 •1. half of 2009 • •Employees •5.1 •5.0 • •Fired •10.3 • • •New • •4.8 • •Firms •6.1 •5.0 • •Fired have the highest hours of sickness. •Source: prezentation Spáčil, Kasal: Projevy krize v datech ISPV, www.trexima.cz kosticky •‹#› •16 Case studies of nominal wages •Who lost job? •Low wages employees •Double sickness absence •Low hours worked •Low qualified •Basic education •It increases average wages, however we need fundamental wages. •It requires expert judgment…how much? kosticky •‹#› •17 Case studies of nominal wages kosticky •‹#› •18 Case studies of nominal wages kosticky •‹#› •19 Case studies of nominal wages kosticky •‹#› •20 Case studies of credit premium •Observation of an increase of credit premium (interbank 3M PRIBOR rates did not follow changes of the 2W CNB’s policy rate) •Associated with uncertainty, releasing worse and worse economic data (at the beginning of 2009) etc. •g3 shows us a trajectory of the interbank rate but does not incorporate policy rate (2W REPO rate) •the setting of 2W REPO rate is based on the model consistent trajectory of 3M PRIBOR interbank rate and a credit premium kosticky •‹#› •21 Case studies of credit premium •Solution outside the model ! necessity of assumption about a premium to recognize required trajectory of the policy rate •Assumption that the premium in the Czech economy corresponds to a European Area premium •Approximation using monthly data: •Cred premt = 3mPribort−(2wRepot+2wRepot+1+2wRepot+2)/3 kosticky •‹#› •22 Case studies of credit premium kosticky •‹#› •23 Case studies of trade fall •Observation of deep and equivalent slumps of export and import volumes •The Czech economy case: large import intensity of exports (not only value added is traded ...) •Because slumps of volumes implies a fall in re-exports, the decrease of GDP is smaller •Explanation: cut-off of some logistics centres with relatively low added value • kosticky •‹#› •24 Case studies of trade fall •g3 is well-suited for this situation and provides a tool for a solution •g3 incorporates the openness technology to capture the different (and significant in reality) growth rates of trade volumes with respect to output growth (re-exports) kosticky •‹#› •25 Case studies of trade fall •Initial conditions (model filtration): we observed a decrease of the openness technology •Part of volume slumps can be attributed to a decrease of openness technology •On the other hand, the near-term-forecast (NTF) reassesses the nowcast of trade volumes in order to have deeper slump of exports than imports (see the figure in the introduction) -> a decrease of output kosticky •‹#› •26 Case studies of car scrapping subsidies •Car scrapping subsidies in some European countries raise demand for Czech cars •Car industry is very significant in the Czech Republic (Skoda, TCPA - Toyota Peugeot Citroen Automobile, Hyundai, many suppliers) •Car scrapping significant mostly for lower class cars (the majority of Czech production) ! we observe an increase of car production, and hence exports •But subsidies in 2009, strong uncertainty for 2010 kosticky •‹#› •27 Case studies of car scrapping subsidies •Foreign demand modelled exogenously •Expert judgement for foreign demand: significant increase in 2009, but a decrease in 2010 with the termination of subsidies •People will exploit subsidies before the termination with subsequent fall in demand for cars •Reference paper: Adda, J. and Cooper R. (2000): Balladurette and Juppette: A Discrete Analysis of Scrapping Subsidies. The Journal of Political Economy 108:4. • kosticky •‹#› •28 Case studies of after crisis SS •Relatively high steady-state growth rates before the crisis •Uncertainty with the after-crisis growth (in the short- as well in the long-run) kosticky •‹#› •29 Case studies of after crisis SS •We keep the same steady-state to have historical filtrations unchanged •But for the forecast the steady-state growth rates of technologies are decreased... •...(assumption about the gradual recovery) •We simulate various scenarios with (lower growth rates in middle-run and long-run, lower wages, negatively shocks to technologies etc.) kosticky •‹#› •30 Scenario analysis •Scenario vs. Fan charts (graphs with confidence intervals) •Scenario analysis is constructed to capture uncertainty of the produced forecast. •Scenario analysis also serves the purpose of gaining better intuition. •Scenarios may differ not only in alternative paths of exogenous variables but also whether and what variables are anticipated or unanticipated. •Our decomposition tools are: •decomposition of alternative scenarios into factors, •analysis of sources of a difference between two successive forecast, •dynamics decomposition of a forecast w.r.t the steady state. kosticky •‹#› •31 Scenario analysis •Nominal wages and productivity •Foreign demand •Energy prices •Exchange rate • kosticky •‹#› •32 Sensitivity to nominal wages and productivity •Four experiments •Observation of higher wages is shock •Observation of higher wages due to higher productivity •Expert judgment of lower wages on forecast is shock •Expert judgment of lower wages on forecast due to lower productivity kosticky •‹#› •33 Sensitivity to nominal wages and productivity kosticky •‹#› •34 Sensitivity to nominal wages and productivity kosticky •‹#› •35 Sensitivity to nominal wages and productivity kosticky •‹#› •36 Sensitivity to foreign demand kosticky •‹#› •37 Sensitivity to energy prices kosticky •‹#› •38 Sensitivity to exchange rate