January 2011 Economic Indicators

Fun, fun, fun. Just like with the CPI, the Department of Statistics has revised the basis of the leading, coincident and lagging economic indicators. The good news is that they’ve rather nicely recalculated the time series for all three based on the new components, and added diffusion indexes. The bad news is that this means a lot of input work for me.

So you’ll just have to read their own take on it, for now.

I’d also call attention to the reference dates for Malaysia’s business cycle, which have been included in the report for the first time. I can’t say enough how important this little nugget is, because it gives researchers and econometricians looking at Malaysia a single point of reference when looking at growth and recession periods, much like the NBER Business Cycle Dating Committee does for the US (note: the term recession here has a different meaning from what it’s usually taken to mean).

You can find the dates at the end of the full report (warning: pdf link), along with information on the construction of the new indices, which are interesting in and of themselves. The fact that seasonal adjustment and HP filters were used (hopefully with the correct cycle parameter), shows DOS are getting confident in their use of best practices. I would have also wished that some of the component indices were also published, like the Retail Sales Index and especially Manufacturing Capacity Utilisation, but beggars can’t be choosers.

Technical Notes:

January 2011 Economic Indicators Report from the Department of Statistics

Economic Data on Malaysia: Where You Can Go

[Update 09 August 2010: This post has been deprecated. I’m maintaining a permanent page for everybody’s reference with updated links here]

I’ve noticed that I’ve gotten quite a few hits through Google looking for data on the Malaysian economy. As a reference point, I’m going to compile in this post the major online-only references that I know of for the basic time series data on Malaysia. If there’s anything readers are looking for that they can’t find, let me know in the comments, and I’ll do my best to oblige. I'd also appreciate it if any broken or wrong hyperlinks are reported.

The one exception to this summary will be historical stock market data, as Bursa Malaysia thinks it can make money off this. In any case, you can get daily KL Composite Index data (from about 1993) from Yahoo! Finance.

I’m listing this by category, rather than by location, as that would probably be more useful. The main sources are:

1. Bank Negara Malaysia (BNM)
2. The Department of Statistics (DOS)
3. The Economic Planning Unit (EPU)

...although I'm also including some international sources. Most reports are either bilingual (English and Bahasa Malaysia) or English only.

One comment before going forward with the list of references: you can get fairly extended time series through Bank Negara’s online version of the Monthly Statistical Bulletin beyond what’s ostensibly published. From about 2004, BNM published the MSB in both Acrobat Reader and MS Excel formats. In the Excel version, older data points are in hidden columns and rows. Just highlight a whole sheet, right click on a column or row header, and click unhide. In most cases, monthly and quarterly data go back to at least 1998-2000, unless there’s been a change in the price series. For 1996-1997 data, it helps to download the older pdf versions of the MSB circa 1997-1998. Enjoy!

Money and Banking
Bank Negara’s Monthly Statistical Bulletin (MSB) is available online from the April 1998 issue, with Sections 1 and 2 covering balance sheet items, while Section 4 covers interest rates. Series covered include banking system asset and liabilities, loan direction, loan sectors and purpose, loan disbursements, repayments and approvals, non-performing loans, with breakdowns for commercial (deposit taking) banks, merchant/investment banks, and the now defunct finance company sectors. On the monetary side, series on M1, M2 and M3 plus their components are available. Interest rate series are available for interbank, government securities as well as deposit and lending rates.

BNM also offers more up-to-date interbank rates for both conventional and Islamic markets.

Gross Domestic Product (real and nominal)
The Economic Planning Unit (EPU) of the Prime Minister’s Department has a summary of GDP tables for annual series (1987 for constant prices, 1947 for nominal prices) and quarterly series (from 2000). Reports are released two months after each quarter end, and are available through DOS (numbers) and BNM (statements). MSB (Section 5) also carries the annual and quarterly series, but not as extensively as EPU.

You can also get both through IMF International Financial Statistics (annual from 1970, quarterly from 1980), plus the volume index which I tend to use as it means you don’t have to deal with the different price bases. IFS is subscription only, but you can get a 5-day free trial which allows full access to the database (discounts available for middle-income countries; free for developing countries). I’d suggest if you’re doing a one-off project like a dissertation or thesis, to register for the trial and download everything.

Annual and quarterly data is also available through the World Bank WDI and IMF World Economic Outlook database, which also have the advantage of carrying PPP-adjusted measures.

Apart from the above, for international comparison purposes, you can also try the Penn World Tables.

Industrial Production
As with CPI, initial reports are carried on the DOS website, while time series can be found in the MSB (Section 5). EPU carries longer time series.

Prices (PPI and CPI)
First reports for CPI are available from DOS, while BNM’s MSB (Section 5) carries the time series. EPU also carries longer annual series. If you need longer monthly series, I suggest the International Labour Organisation, which provides a linked series across different base years (which saves you the trouble of doing it yourself).

PPI is far more troublesome. First DOS does not issue online reports, while the MSB only carries annual and monthly changes (not the index numbers themselves). In short, you have to reconstruct the index yourself if you use MSB as a source. EPU however does carry the annual index series (and monthly series from 2003), although you’ll have trouble with the fairly frequent change of base year.

Employment/Unemployment
You’re out of luck.

Employment/unemployment stats have the worst online coverage of any of the major economic statistical categories for Malaysia. DOS carries a monthly manufacturing survey that only covers wages and employment in that sector. MSB is more comprehensive, covering retrenchments, active job seekers and employment offerings by sector, but not an overall unemployment number. The EPU offers annual unemployment statistics, which aren’t terribly useful for current analysis.

Population
Population estimates are available from EPU. DOS also has a population clock on its homepage (MSIE only), with an explanation of the assumptions here.

Poverty
Poverty estimates are also available from EPU. Poverty Line Income data however is unfortunately not readily available, nor are income inequality measures. I have a compilation of Gini coefficient numbers lifted from this book, but since I can’t reconcile the numbers with those published in the various Economic Reports, I’d hesitate to place too much reliance in them.

Government Finance
BNM’s MSB, section 6, covers breakdowns of quarterly and annual of federal government revenue sources, expenditure, and composition and holders of government debt. EPU provides annual series going back to 1970, and more interestingly, annual consolidated accounts for the public sector from 1991.

Forex (Ringgit) spot rates
Believe it or not, the best source I’ve found is the Federal Reserve – they carry daily currency fixes against the USD for a whole bunch of currencies (report H.10*). In the case of MYR, this extends back to 1971. For shorter periods, I use the Pacific Exchange Rate Service, which carries four years of daily data and monthly averages for more extended periods. I find it especially useful since you can download cross-rates directly instead of having to calculate them yourself. BNM also carries daily currency fixes (from 1997), and 3-month and 6-month forward rates (from 1999).

*2000 to present, 1990-1999, pre-1990

Balance of Payments
Balance of Payments are reported quarterly. The latest data is available through DOS, and more extensive quarterly and annual series are available from MSB (Section 7). A longer annual series is available from EPU.

International Investment Position
The IIP is a relatively new metric designed by the IMF to track holdings of foreign assets: don’t expect extensive time series on this. The numbers from 2005 are available from DOS or IMF IFS database.

External trade
The actual report is issued by MATRADE, which DOS mirrors. Time series and detailed breakdowns are available with a lag through MSB (Section 7) or through EPU. If you need deeper breakdowns, I suggest (unless you want to wade through DOS’ veeerrryy thick annual trade reports) the United Nations Commodity Trade Database. It’s not comprehensive*, but reasonably complete enough for most purposes.

*Like almost all multilateral institutions, the UN doesn’t carry data on Taiwan – an example of politics getting in the way of common sense.

International Reserves
Reserves are reported biweekly and detailed reports are available from BNM. MSB Section 7 carries the time series.

Leading, Coincident and Lagging Indicators
DOS provides the latest data, with an archive available here. EPU also has much longer monthly series available. The Malaysian Institute of Economic Research’s quarterly Business Conditions Index and Consumer Sentiment Index and MIDA’s investment approval statistics are also available through the latter link.

Miscellanea
1. The annually published Economic Reports, prepared in conjunction with the tabling of the government budget, are available through the Ministry of Finance. Extensive statistical tables are available at the back of each edition.

2. BNM’s annual reports provide useful overviews of monetary and financial sector developments. Quarterly reports are also available.

3. Links to Malaysia’s 5 year plans (current and archived from 1995) are available through EPU's homepage. You'll find here, among others, income, poverty and inequality data.

4. The Financial Sector Masterplan outlines the program of financial sector reform 2000-2010.

5. The Capital Markets Masterplan does the same for debt and equity markets, and is available through the Securities Commission.

6. Information on Malaysia's countercyclical stimulus pacakages are available here.

7. Malaysia's National Summary Data Page is available through BNM.

Leading Indicators: Not So Good After All

When I did my first evaluation of the Composite Leading Index issued by DOS, it was based on a relatively short sample (from 2005-2008). The results were generally good, with the Leading index approximating movements in real GDP. I've since found a more complete source for the index series, covering 1999-2009. Redoing my forecast models for GDP yielded some disappointing results.

First, fitting the regression became more complicated, with diagnostics revealing serial correlation and heteroscedasticity, which required fitting an ARIMA model (with heteroscedasticity-corrected standard errors) to the data rather than a purely deterministic one. Second, while the Leading Index showed a good fit for most of the sample, the relationship basically breaks down right at the beginning of the downturn in 2008:4. The following shows the model using seasonally adjusted rGDP:


LOG(RGDP_2005R_SA) = 0.365*LOG(IND_LEAD) + 9.992 + [AR(1)=0.973] (R2=0.992)

...and using seasonal dummies:


LOG(RGDP_2005_R) = 0.349*LOG(IND_LEAD) + 10.051 + 0.023*D2 + 0.052*D3 + 0.046*D4 + [AR(1)=0.973] (R2=0.992)

In both models, the residual breaks sharply from the standard error line, which represents about 70% of probable observations assuming a normal distribution. The seasonally adjusted model indicates that the fall in 2009:1 rGDP was a 4 standard error event (a probability of 0.003%), while the seasonal dummy model indicates a 2.8 standard error event (a probability of 0.2%).

In short, this downturn is something out of the ordinary even for a recession. The Leading Index is in fact currently out of step with the economy, and would overstate GDP if used as a basis for forecasting. In comparison, the residual in the short 2000 recession was barely out of the 1 standard error line, and that only in the second model.

To be fair, the Leading Index is not constructed as a direct representative of movements in GDP, but rather an indicator of turning points in economic activity. Also, my data only covers from 1999-2009, which really is just one full business cycle. On that basis, there may be some hope that the DOS forecast of a turnaround in the economy in 2009:3 may come true. But I'm not holding my breath.

Indicators For The Economy: Leads, Lags, and Coincidence

One common complaint from just about everyone is that economic data comes out at a fairly big lag. Malaysian quarterly GDP reports typically come out two months after the fact, which makes informed decision making difficult at best. I've laid out some of the reasons for the lag in this post here.

There are however some indicators that can give you a fairly accurate representation of what the economy is doing at much faster frequencies. The Department of Statistics issues monthly composite indexes that do exactly that. The Lagging Index is supposed to affirm the trajectory of the economy after the fact, the Coincident Index shows what the economy is doing right now, while the Leading Index gives an idea of how the economy will do in the future about 1 or 2 quarters ahead.

Here's what the indexes are showing up to February 2009:




All the Indexes are turning up, which gives some comfort that things are turning around. But how good really are these indexes relative to actual economic performance? The answer is: except for the Lagging Index surprisingly good.

I evaluated all three against real GDP (sample range 2005:1 to 2008:4), using both seasonal adjustment (x11) and with seasonal dummies. The quarterly index numbers are arrived at by averaging the monthly index numbers.

Only the Lagging Index didn't fit at all well. In terms of forecasting, the Coincident Index fit well in-sample but not forecasting out of sample (charts and results shown are for the non-seasonally adjusted regressions):

In-Sample Forecast (2005:1 to 2008:4):



LOG(RGDP_2005) = -0.63*LOG(IND_COIN) + 2.38*LOG(IND_COIN(-1)) + 3.36 + 0.01*D2 + 0.04*D3 + 0.03*D4

Out of Sample Forecast (2005:1 to 2007:4; dynamic forecast to 2009:1):



LOG(RGDP_2005) = 1.6729687*LOG(IND_COIN) + 3.69 + 0.01*D2 + 0.04*D3 + 0.04*D4

The Leading Index on the other hand is remarkably accurate:

In-Sample Forecast (2005:1 to 2008:4):



LOG(RGDP_2005) = 1.01*LOG(IND_LEAD) + 6.67 + 0.01*D2 + 0.04*D3 + 0.03*D4

Out of Sample Forecast (2005:1 to 2007:4; dynamic forecast to 2009:1):



LOG(RGDP_2005) = 1.02*LOG(IND_LEAD) + 6.63 + 0.01*D2 + 0.03*D3 + 0.03*D4

I admit to being surprised by these results. I would've thought the Lagging Index to be most accurate, and the Leading Index the least accurate - it turns out the opposite is true. The forecast standard error for the Leading Index is actually half that of the Coincident Index. I'd caution however that the above analysis is based on a rather short sample (reminder to self: a trip to DOS seems warranted). I'd love to know the exact composition of the Indexes and the source data - cointegration analysis would give a good idea of short term dynamics, as well as the relative importance of each component.

What does the Leading Index forecast say about 2009:1Q GDP? Based on the full sample:

Point forecast: RM128,236.1
Upper Bound: RM130,497.9
Lower Bound: RM125,974.4

The point forecast is equivalent to -0.7% growth y-o-y, and -9.5% growth q-o-q annualised, both down from 4Q 2008 growth but rather better than I expected. We'll see how accurate this is when the 1Q 2009 report comes out at the end of this month.