DOS gets an upgrade

Read here. Data collection for Census 2010 will apparently be internet-based.

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.

Down The Slippery Slope: January IPI

A picture is worth a thousand words (log changes in IPI over the same period last year):



and here's the month on month (log changes in IPI over the previous month):



Unfortunately, DOS have changed the base of the index to 2005 starting this month, which precludes any deeper analysis until I get my hands on the complete time series and splice it into the old one. It's clear however that the carnage is largely in manufacturing.

The Pitfalls of Econometrics

de minimis has an interesting post advocating using more econometric models to guide policy making in Malaysia. While I tend to lean that way myself (there's too much unsubstantiated rhetoric flung around the news and blogosphere for my taste), I don't want to be blind to the potential pitfalls and shortcomings of an applied econometric approach to policy. So this post is both to clarify some of the issues, as well as serve as a reminder to myself not to be too "assertive", as my wife puts it.

First is that econometric modeling (as etheorist remarked the other day) is really an art, not a science. There are many, many ways of looking at an economy and generating forecasts, from simple time series techniques to hideously complex dynamic general equilibrium models. So model choice and specification (as well as accompanying underlying assumptions), and not to mention the ideological bent of the modelers, can lead to very different conclusions about the state of the economy at any given time. The issue is compounded by Malaysia being such an open economy, which means that ideally, you'd have to incorporate all the major trade partners into your model as well.

Secondly, the evolving economic structure within a developing country means that even if you do come up with a model close to reality at some point in time, it might be out of date very quickly later on and you won’t know it until something goes wrong. This is one point where I would be critical of DOS: the Malaysian input-output tables haven’t been updated in years, and you need this to model intra-industry dynamics.

Thirdly, any econometric model necessarily uses historical data, which means there will always be an unobservable error component in any forecast in the presence of a current shock. A corollary of this is that, almost by definition, a trade shock such as we just suffered cannot be predicted on the basis of concurrent data. Models are more useful as a predictive guide to inventory driven recessions and business cycle downturns. You can of course use models to predict what happens when a shock occurs, but not when or if a shock will occur.

Fourth, data accuracy is inversely proportionate to the speed at which data is published. In other words, the faster you publish it, the larger the error rate. Where I think DOS can improve on that score is to follow the general practice in the EU, US and yes, Singapore, i.e. issue advanced, preliminary, and final estimates of major statistical series. The current practice of a 6-week to 8-week lag and quietly revising the historical series, isn't transparent (the loose hair around my workplace is testament to that). Data revisions should always be made clear, especially for national accounts data, which has to be revised even 2-3 years down the road.

One exception to this observation is financial sector data, which is available very quickly. (Side note: I've visited BNM to study their data gathering process, and I was a member of one of the teams responsible for implementing CCRIS in one of our banks - I am very impressed with BNM's operation in this instance. The disaggregated trial balance of the entire banking system is available at about t+4 after every month end – in other words, don’t be fooled by the monthly publishing schedule). (Side note to the side note: this is one reason why monetary policy is generally the first recourse in any crisis – you have better data much faster than real economy data).

However, I should point out that a 2-month to 3-month lag hits the sweet spot between accuracy and timeliness, and is fairly typical worldwide. China for instance tends to issue data on a 1 month lag, but subsequent revisions tend to be very large. Some Canadian series have no revisions at all, but you have to wait 6 months(!) to get them. I cannot fault DOS on that score, though they have made some absolute boo-boos before (pay attention to 2004-2005 trade data before and after revision, for instance).

Fourth: some of the most critical variables required for a predictive model are unobservable. For example, consumer and investor expectations have a big impact on private consumption and investment, but can’t be quantified. It’s possible to use proxies, such as consumer confidence or business expectations surveys, but these are subject to error as well.

Take all the factors above, and you shouldn’t be surprised that most whole economy econometric models have very little predictive power more than a quarter or two ahead, out of sample. I’d note that I’d be very surprised if the government doesn’t have on hand some whole economy econometric models, especially for trade and tax policies. Could more use be made of modeling? Absolutely! Just don’t fall for the promise that they’ll be a panacea and perfect guide to policy.