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Maldives National Macroeconomic Forecasting And Policy Simulation Models Content • Maldivian Economy • Forecasting Models • • • • Process Tourist Arrivals GDP Revenues Real Sector Co-Movement of GDP and Tourism 25% 60% 20% 15% 40% 10% 20% 5% 0% 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 0% 2003 • Real GDP per capita in 2015: US$ 6,088.68 (projected) • High dependency on tourism ‐ contributes about 30% to GDP • Highly susceptible to external shocks • Share of fisheries sector is small, but still a key source of employment for many • Unemployment rate (broad definition): 28% in 2010 ‐5% Financial crisis ‐10% ‐20% Indian Ocean tsunami ‐40% ‐15% Tourism Sector Growth (Right Axis) Real GDP Growth (Left Axis) Real Sector ‐ Prices Inflation 20% Introduction of GST 18% 16% 14% Rufiyaa devaluation 12% 10% 8% 6% 4% 2% 0% Q1‐2009 Q2‐2009 Q3‐2009 Q4‐2009 Q1‐2010 Q2‐2010 Q3‐2010 Q4‐2010 Q1‐2011 Q2‐2011 Q3‐2011 Q4‐2011 Q1‐2012 Q2‐2012 Q3‐2012 Q4‐2012 Q1‐2013 Q2‐2013 Q3‐2013 Q4‐2013 Q1‐2014 Q2‐2014 Q3‐2014 Q4‐2014 Q1‐2015 Q2‐2015 • Inflation peaked in early 2012, reflecting the introduction of the GST and the devaluation of rufiyaa • Gradually back to lower levels as these one off effects dissipated • Food has a weight of 23.8% in the CPI basket • Exchange rate pass through is extremely high, and international commodity price changes are reflected to a high degree Inflation Inflation excluding fish Fiscal Sector Revenue, Expenditure and Financing (% of GDP) • Government expenditure consistently exceeds revenue • Major revenue source was the import duty until 2011 • Now, GST (especially T‐GST) and the business profit tax are the main sources, and import duty rates have been reduced • Largest share of government expenditure goes to employee remuneration • 70% of total expenditure is recurrent expenditure 20% 160% 18% 140% 16% 120% 14% 100% 12% 80% 10% 8% 60% 6% 40% 4% 20% 2% 0% 0% 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Total revenue and grants (% of GDP, left axis) Total expenditure and net lending (% of GDP, left axis) Deficit (% of GDP, right axis) • Total debt has been rising sharply since 2008, mainly fuelled by rising domestic debt • Newly introduced fiscal responsibility act stipulates that the debt‐to‐GDP ratio should be at most 60% by the end of 2016, and maintained below the threshold thereafter 80% 35,000 70% 30,000 60% 25,000 50% 20,000 40% 15,000 30% 10,000 20% 5,000 10% 0% ‐ 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total debt (right axis) External Debt to GDP (left axis) Debt to GDP (left axis) Millions of Rufiyaa Fiscal Sector ‐ Debt External Sector ‐ Trade • Trade deficit is expected to be at 56% of GDP in 2015 • Services account surplus is expected to be at 72% of GDP in 2015 2500 2000 Millions of USD • Have consistently been experiencing trade deficits • Current account deficit is expected to be at 7% of GDP in 2015 1500 1000 500 0 2005 2006 2007 2008 Domestic exports f.o.b. 2009 2010 2011 2012 Imports f.o.b. 2013 2014 2015 Trade deficit External Sector ‐ Reserves • Gross international reserves consist of the reserve assets held by MMA 5.0 • Built up mainly through tourism sector activity (tax receipts) and the accumulation of foreign currency assets by banks 3.5 • Challenge to intervene in FOREX market due to low reserve levels • Reserves improving in recent years 800 4.5 700 4.0 500 3.0 400 Months 2.5 2.0 300 1.5 200 1.0 100 0.5 ‐ 0 2009 2010 2011 2012 2013 2014 Gross international reserves (right axis) Gross international reserves import coverage (left axis) Jun‐15 Millions of USD 600 Monetary Sector – Credit Growth • Global financial crisis • Deterioration in the asset quality of banks (increase in NPLs) • Diverted to investment in T‐bills 18,000.0 16,000.0 14,000.0 Millions of Rufiyaa • Rapid increase in credit to government after 2008 partly reflects the widening fiscal deficit • Expansion of credit to private sector stalled after 2008 12,000.0 10,000.0 8,000.0 6,000.0 4,000.0 2,000.0 ‐ 2005 2006 2007 2008 2009 Credit to central government 2010 2011 2012 2013 2014 Jul‐15 Credit to private sector Monetary Sector – Interest Rates T-bill Interest Rates • This did not reduce T‐bill investment, reflecting the lack of other investment opportunities in the domestic market • T‐bill interest rates mechanically halved in November2015. 11 10 9 8 Percent • Interest rates increased dramatically for T‐bills of all maturities reflecting the widening fiscal deficit • Tap system introduced in 2014 to curb the increasing interest burden on the government 7 6 5 4 3 2007 2008 28 days T‐bill 2009 2010 90 daysT‐bill 2011 2012 2013 182 days T‐bill 2014 Nov‐15 364 days T‐bill Forecasting Process Macro Modeling • Budget Process • Macroeconomic Policy Coordination Committee • Medium‐term budgets • Policy approval • Medium Term Economic Framework • • • • Being built with the help of World Bank Brings together isolate models Behavioral linkages Excel based Forecasting Models GDP Procedural Change National Bureau of Statistics (NBS) to discontinue production of annual medium term GDP forecasts‐ from 2015 NBS to produce Quarterly National Accounts(QNA) –first release 20th October • NBS will produce actual GDP, quarterly and annually • Not the international best practice for statistical agencies to produce annual forecasts EDPD/MoFT to produce annual forecasts for GDP growth and Nominal GDP Forecasting model Univariate time series model • Using the Quartely Real GDP series (2003Q1 to 2015Q2) • Model using information on its own past values • AR (1 ,4 ) SARIMA(0,1,0)4 model Advantages • Simple to model • Often found to produce better forecasts than structural models • Incorporates information of the economic growth up to Q2 2015 Disadvantages • Retrospective • Cannot dissect the growth impact of specific items • A‐theoretical Forecast – Univariate time series model GDP GROWTH:2015‐2018 8.00% 7.50% 7.00% 6.50% 6.00% 5.50% 5.00% 4.50% 4.00% 2015 2016 2017 Annual GDP ARIMA(1,1,0) model Annual GDP External Demand Model QRGDP Trend + AR(1) + Seasonal dummies QRGDP AR(1,4) + SARIMA(0,1,0,4) 2018 NGDP Forecasting method GDP (EXP) 2014 GDP 2014 GDP Expenditure breakdowns C Forecast growth for indicators 2015‐2018 Imports of Household Consumptio n Goods Indicator Weights 1 G I X (goods) X (services) M Wage bill budget and forecast Intermediat e consumptio n costs budget and forecast Imports of capital goods Imports of building material Govt Capital Expenditure budget and forecast Exports of goods Tourism Bednights Imports of goods Wage bill budget and forecast Govt Capital Expenditure budget and forecast 0.75 0.25 0.6 0.3 0.1 1 1 0.9 0.05 0.05 Nominal GDP Series‐ October 2014 update 70000 35% 30% 60000 25% 50000 40000 15% 10% 30000 5% 20000 0% 10000 ‐5% ‐10% 0 2001 2002 2003 2004 Source : National Bureau of Statistics (October 2014) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Growth MVR millions 20% Issues with GDP forecasting • Disconnected methods to forecast RGD and NGDP • Not a critically scrutinized model Forecasting Models Tourist Arrivals Medium term forecasts • A global tourism elasticity‐based model for medium term forecasts • Maldives is hyper‐sensitive to global tourism, with an estimated elasticity of 184 percent Medium term model • LOG(ARR_MDV) = C(1) + C(2)*LOG(ARR_GLOBAL) + C(3)*SHOCK + AR(1) • Global arrivals forecasts from UNWTO is included. Within year forecast • Temporal (or seasonal) based model for within year forecasts • Seasonal patterns apparent and consistent • High dependency on European tourists, peak season in Maldives corresponds to European winter months of December‐February. • However, since of late China has emerged as the single largest source of tourists and also the one which has shown the strongest growth. Interestingly, Chinese arrivals also reflect strong seasonal features but with effects opposite to that of the European segment. Within year (short term) model • Calculate weights for main markets, namely, China, Europe and RoW. • Run AR models for each market • Multiply forecasts from AR models with weights to obtain short term monthly forecasts Issues and updates • Both models have relatively large standard errors. • Shock variable (a binary variable) is exogenous to the model and is captured for only 1 period. This is not very robust and a better approach would be to have some indication of duration of a shock through an appropriate formulation. • Models performed poorly in recent years. • New research to update the model on‐going. Forecasting Models Revenues Revenue Forecasting • Historically done by collecting agencies. • New Medium Term Economic Framework (MTEF) being built. Same models are incorporated to the MTEF. • Over 90% of 2014 MIRA revenue comprise of 7 revenue codes: • • • • • • • GST (Tourism and Non‐Tourism Sectors) BPT Tourism Land Rent Tourism Tax / Green Tax Lease Period Extension Fee Bank Profit Tax Airport Service Charge MVR billions MIRA Revenue 14 11.50 12 8.98 10 7.15 8 6 4 4.56 2.41 2 0 2010 2011 2012 2013 2014 Others Airport Service Charge Bank Profit Tax Lease Period Extension Fee Tourism Tax Tourism Land Rent BPT GST Total Tourism Sector GST • Bednights information and forecast – from the Ministry of Tourism • Spending Rate • Calculate the ‘consumption’ of the tourism sector • Equals to TGST collection / TGST rate • Calculate Spending per tourist per bednight (spending rate) • Tourism sector consumption / bednights • Estimate the spending rate for the projection period • Take a moving average of the past years’ spending rate • Increase it by a rate indicative to the growth in past year’s spending rate and inflation • TGST revenue = Spending Rate x Bednights x TGST Rate Spending Rate 500 450 400 350 300 250 200 150 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2011 2012 2013 2015 2016 2017 2014 Non‐Tourism Sector GST • Calculate the consumption subject to GST in the non‐tourism sector • Equals to GGST collection / GGST Rate • Analyse the consumption trends • Analyse GDP and inflation • GDP forecast not available at the time of projection • Estimate a crude growth rate for the real GDP based on past growth rates • Estimate a crude inflation figure for the projection period based on past figures • Estimate nominal GDP growth based on inflation and real GDP growth rate • Estimate the consumption for the projection period based on moving average of past consumption levels, increased by nominal GDP growth rate. • Additional weight may be necessary to reflect growing compliance • GGST revenue = Consumption x GGST Rate Airport Service Charge • Tourist arrivals estimates are obtained from the Ministry of Tourism • Calculate the share of foreign departures based on information obtained from Airport operators • Share of foreigners in the total departures: 88.4% • Share of tourists among foreign departures: 92.1% • Estimate foreign departures • Tourist arrivals divided by ‘share of tourists among foreign departures’ • Estimate total departures • Foreign departures divided by ‘share of foriegners in the total departures’ • Estimate Maldivian departures to abroad • Total departures minus foreign departures • Multiply with respective ASC rates • USD 25 for foreigners and USD 12 for Maldivians • Airport Service Charge = ASC from Foreigners + ASC from Maldivians Economic Forecasting in Maldives • Various models, various institutions and various software. • The teams involved in forecasting have close dialogue and work together on some models (eg: new tourist arrivals model)