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Economics WDYT

[2851] Guess the 1Q17 Malaysian GDP growth

The first quarter 2017 Malaysian GDP figures will be out on May 19. So…

Industrial production in 1Q17 did not grow as strongly as it did in the previous quarter. Nevertheless, manufacturing had swell of a time. Trade figures were very good, with both goods exports and imports grew double digits, which indicates both the external and the domestic demands are somewhat healthy. But in terms of net exports, I do not think it would contribute much to the GDP growth since import growth was stronger than export expansion.

Talking about the domestic market, the unemployment rate seems to have finally responded to the better economic environment. Eyeballing, the seasonally-adjusted UE for the quarter is about 0.2 percentage points lower than what seems to be the average for 2016. Core inflation is slightly up, also showing domestic demand is recovering, assuming this core inflation calculation by the Department of Statistics completely isolates cost-push inflation.

By the way, the 4Q16 GDP grew 4.5% YoY.

How fast do you think did the Malaysian economy expand in 1Q17 from a year ago?

  • 3.5% or slower (0%, 0 Votes)
  • 3.6%-4.0% (0%, 0 Votes)
  • 4.1%-4.5% (29%, 2 Votes)
  • 4.6%-5.0% (29%, 2 Votes)
  • 5.1%-5.5% (14%, 1 Votes)
  • Faster than 5.5% (29%, 2 Votes)

Total Voters: 7

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Economics

[2850] The arbitrariness and the superficiality of Malaysia’s $15,000 high-income nation benchmark

In the past week or so, there were several news reports stating that Malaysia was regressing backward relative to the high-income country GNI benchmark of $15,000 per person by 2020. The Economic Planning Unit showed the figure fell to $9,291 in 2015 and to $8,821 in 2016, from $10,677 in 2014.[1]

From the figures alone, it is plain to see that the gap between current level and the $15,000 per capita has increased. The 2020 target was set by the government as the benchmark Malaysia needed to hit to in order to declare the country as a “high-income nation.”[2] Pemandu’s whole reason for existence is predicated on this.

But such conclusion (and the target itself) is superficial and largely a non-issue as far as economic growth is concerned. What is more important in terms of development is the levels of welfare, which is better represented by the purchasing power parity calculation, instead of the Atlas method used to calculate the GNI per capita figures in the US dollar.

There are three reasons why I claim the conclusion is superficial.

First, the $15,000 GNI per capita by 2020 target is susceptible to foreign exchange rate fluctuation. This is despite the Atlas method is designed to minimize the same fluctuation. The ringgit depreciation relative to the US dollar in 2015 and 2016 was just too big for the method to handle. Its inability to control for the fluctuation makes its output less reliable that it normally is. You can see why it does a bad job within the context of 2015 and 2016: the Atlas method controls the forex rate variation by averaging the latest three years of the relevant rates (the method does include inflation differential between countries but it is not nearly as good as the PPP). But even under normal circumstance, the Atlas method is inferior to the purchasing power parity just because the former does not adjust for domestic living costs properly. The PPP may have its own failings but its failings are considerably less serious than the Atlas method.

To understand this point further, we have to realize that for most Malaysians, earning and spending are carried out in the local currency, the ringgit. Only a small minority earn in ringgit but spend in foreign currency, among them the US dollar. So for most Malaysians, it is unclear why the size of the economy translated through the Atlas method into the US dollar is meaningful in determining the state of a country’s development level or its population welfare, apart from the fact that the World Bank uses it and that Pemandu was just following suit.

The World Bank states it is using the Atlas method for operational purposes,[3] which makes sense because the organization lends money to national governments mostly in major currencies and that the repayments are susceptible to the forex fluctuation due to currency mismatch. They need to take the forex fluctuation into account.

Meanwhile, Pemandu and Malaysia use it as a target… because the World Bank uses it for its global lending purposes done largely in US dollar. You can see the problem here. The World Bank’s and Malaysia’s purposes for using the Atlas method are vastly different. It fits the World Bank’s goal better than Malaysia’s. PPP, on the underhand, fits Malaysia’s purpose better than the World Bank’s. It is a case of using the wrong tool.

Second, even if we accept the target and the Atlas method wholly, the actual benchmark for high-income is likely lower than the $15,000 barrier. The $15,000 benchmark itself did not come from the World Bank but projected into the future by Pemandu based on figures from the international body. The latest 2017 high-income benchmark actually used by the World Bank is $12,476.[4] Pemandu had projected the figure from 2010 (if I am not mistaken), assuming the 2010-2020 growth rate of high-income countries to average 2.0% yearly. The reality is that the 2010-2017 average is only 0.2% yearly so far. At the current actual growth rate, the benchmark will be $12,563 per capita by 2020 assuming everything else remains the same. It is still a widening gap, but not as bad as when the $15,000 per capita is the target.

Third, the implications of the conclusion are outrageous, if the Atlas method completely addresses concerns over forex fluctuation: either Malaysia had run into a two-year long recession, or we had an extraordinary population boom during the same period.

But we did not have a recession. We did have a growth slowdown however. The Malaysian economy grew by 5.0% in 2015 and 4.2% in 2016. But no recession, which is a contraction of the GDP by two consecutive quarters.

And we did not have a population boom either during the two years. The size of the Malaysian population in 2015 and 2016 grew 1.4%-1.6% yearly, lower than in the previous years.

Since both did not happen (with inflation was not big enough to matter: Malaysia’s 2%-3% and in the US, 0%-1%), we must question the validity of the Atlas method in measuring the well-being of Malaysians. And by extension, it questions the ability of the Atlas method to determine the status of Malaysia as a high-income nation. The one factor that changed was the forex rate.

But ultimately, the term high-income nation itself is fluffy. There are attempts to give it concrete meaning but would crossing the not too distance line suddenly transform Malaysia into a rich country? It is never as clear as that. While Malaysia has done well compared to a lot of countries in the world, entrance to “first world” is actually harder then merely cross the line defined by the World Bank or Pemandu. Just cross over to Singapore, or visit Japan, or Australia or any of the generally recognized high-income countries. Would Malaysia crossing the GNI per capita $12,475 line suddenly make the us like those countries? Maybe someday, but the barrier will be way above the World Bank’s line.

You know a high-income country when you see one: some classifications are looser than others and many of them are arbitrary. This is the limits of mathematics and economics. So, be careful of turning a soft arbitrary line in the sand as your true north. Managing a country’s development is not like running a business.

But coming back to the original point, no, we have not regressed in terms of economic development. We have regressed in other aspects, like our institutions, but the economy has grown, contrary to what the imperfect Atlas method tells us. If you really want to make an international comparison, the purchasing power parity model is far superior than the Atlas method, especially at a time when forex fluctuation is great.

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[1] — Page 5.The Malaysian Economy in Figures 2016. Economic Planning Unit

[2] — Page 59. Economic Transformation Programme: A Roadmap for Malaysia. October 26 2010

[3] — The income groupings use GNI per capita (in U.S. dollars, converted from local currency using the Atlas method) since they follow the same methodology used by the World Bank when determining its operational lending policy. While it is understood that GNI per capita does not completely summarize a country’s level of development or measure welfare, it has proved to be a useful and easily available indicator that is closely correlated with other, nonmonetary measures of the quality of life, such as life expectancy at birth, mortality rates of children, and enrollment rates in school. [Why use GNI per capita to classify economies into income groupings? The World Bank. Accessed March 23 2017]

[4] — For the current 2017 fiscal year, low-income economies are defined as those with a GNI per capita, calculated using the World Bank Atlas method, of $1,025 or less in 2015; lower middle-income economies are those with a GNI per capita between $1,026 and $4,035; upper middle-income economies are those with a GNI per capita between $4,036 and $12,475; high-income economies are those with a GNI per capita of $12,476 or more. [World Bank Country and Lending Groups The World Bank. Accessed March 24 2017]

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Economics

[2849] The next step: from cash transfer to negative income tax

One of the better things Malaysia experienced on the policy front is the abolition of fuel subsidy and the introduction of targeted/conditional cash transfer as a replacement.

While the mean-tested nature of the transfer has been less the ideal (due to loose conditions) and appears uncorrelated to what the subsidy would have been (its discretionary nature means the transfer policy is increasingly digressing from its original purpose), the policy is still better than the very costly and inefficient subsidy regime Malaysia had. I have advocated the shift from subsidy to cash transfer for a very long time now, and I still support it.

But cash transfer should not be the end of progress. Perhaps the next step is to push the conditional cash transfer towards a more rule-based approach. In that spirit, I think the next step is the introduction of negative income tax system to replace the cash transfer system that we have now.

A negative income tax system works like this: it pays a registered taxpayer money if the person earns below a certain income level determined by the government. One easy benchmark would be the minimum wage level (in doing so, it could make minimum wage policy obsolete). The size of the payment could be a portion of the difference between the determined level and the person’s income.

In short, if you earn below that benchmark, the government pays you some money. If you earn above it, you pay tax. A brief introduction to the policy is available at the Library of Economics and Liberty.[1]

The current cash transfer program Malaysia has, BR1M, has some resemblance to the negative income tax. Those earning below a certain income threshold get the cash transfer. Negative income tax does the same thing, but more.

It goes further by institutionalizing the cash transfer arrangement and eliminates the latter’s discretionary nature, which is susceptible to corruption in its widest sense. It guarantees the payment will be paid out every year based on transparent formula. There will be no grand announcement about the payments by ministers, party members, leeches and definitely no more mock-checks and unnecessary conflict of interest/suspicious handover ceremonies.

The institutionalization also brings about one thing: a real basic income for all Malaysians. It is also an automatic stabilizer for the economy, which means in case of economic troubles, the urge for discretionary fiscal stimulus can be reduced. That also means less corruption on the procurement side.

Payments itself can be done just like how tax returns are done every year. If cashflow is of concerned, the payments can be broken up in stages just like how BR1M is being paid this year.

I do not think the jump will be that big, unlike the previous shift from fuel subsidy to cash transfer. But I do think in terms of benefits, it might be bigger the cash transfer as it could make redundant other welfare policies while streamlining administration cost of supplying or enforcing these other policies.

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[1] — The NIT would thus be a mirror image of the regular tax system. Instead of tax liabilities varying positively with income according to a tax rate schedule, benefits would vary inversely with income according to a negative tax rate (or benefit-reduction) schedule. If, for example, the threshold for positive tax liability for a family of four was, say, $10,000, a family with only $8,000 of annual income would, given a negative tax rate of 25 percent, receive a check from the Treasury worth $500 (25 percent of the $2,000 difference between its $8,000 income and the $10,000 threshold). A family with zero income would receive $2,500. [Jodie T. Allen. Negative Income Tax. Library of Economics and Liberty. Accessed February 15 2017]

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Economics WDYT

[2848] Guess the 4Q16 Malaysian GDP growth

The final quarterly GDP figures will out next week on February 16. The GDP grew 4.3% YoY in the third quarter, up from 4.0% YoY in 2Q16. In the first quarter of 2016, it was 4.2% YoY. So, as the game goes…

How fast do you think did the Malaysian economy expand in 4Q16 from a year ago?

  • 3.0% or slower (13%, 3 Votes)
  • 3.1%-3.5% (0%, 0 Votes)
  • 3.6%-4.0% (9%, 2 Votes)
  • 4.1%-4.5% (35%, 8 Votes)
  • 4.6%-5.0% (39%, 9 Votes)
  • 5.1%-5.5% (0%, 0 Votes)
  • Faster than 5.5% (4%, 1 Votes)

Total Voters: 23

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Judging from industrial and import figures, I would think the domestic demand part of the economy grew reasonably okay in the fourth quarter although other statistics like car sales remain depressed, suggesting not all is well.

The labor market says as much. Unemployment rate is relatively high at 3.6%. That suggests the recent economic growth recovery has not brightened up the labor market. It is not that there is no job creation, but the pace of job creation is not happening as fast as the growth of the labor force.

(Interestingly, the core inflation has been stable at about 2.0%-2.2% in annual terms. Nerdy stuff to note: core inflation fell as unemployment rate rose. This is cool, assuming the GST had minimal impact on the core inflation. Cool because unemployment rate and demand-pull inflation that the core is supposed to measure tell something about the output gap: it may suggest the gap has not changed by much despite 2015-2016 economic weakness. One would start to worry if unemployment rate goes up but core inflation remains unchanged, which suggests the output gap might be widening. A worse worry is when unemployment rate goes up together with core inflation: gap is shrinking but potential is decreasing)

The other good news is that exports did great. But with strong import growth, trade balance for the quarter will not help the GDP. Indeed, from the merchandize goods trade stats, 4Q16 net exports actually fell in the quarter by nearly 10% YoY.

So, in the end, I am thinking the 4Q16 GDP growth will be somewhere in the mid-4.0%, leaving the full year 2016 GDP growth at 4.2%-4.3%.

Categories
Economics

[2846] Unfairly casting aspersion on the Gini coefficient

There is a very good article published in the Malay Mail over the weekend.[1] It is about the brisk sales of high-end cars like BMW and Mercedes in Malaysia while entry-level, compact cars like Perodua are doing badly, and the consumption pattern in the economy by income levels.

[The divergence car sales by prices are part of the weird macroeconomic statistics that have been coming out of Malaysia since the GST was introduced back in April 2015, along with the collapse of oil prices. Weirdness like the consumption growth is rising nicely while big ticket items like cars and homes are not doing so well in terms of growth. In fact for cars as a whole, it has been declining. It may be some non-business cycle explanation behind this, like the widening of train network in Malaysia but for now (a person driving BMW rarely if ever take the train, for instance), let’s put that aside and maybe discuss that on another day.]

But I have one, tiny issue with the article, way, way down. The author questions the accuracy of the 2014 Gini coefficient, which suggests inequality, decreased compared to 2012, while pointing to the latest car statistics (2015-2016), which may say otherwise:

While BMW Malaysia posted its highest ever sales growth last year, its rival Mercedes posted record sales for the second straight year in 2016. A total of 9,047 Mercedes vehicles reported to have left its showrooms in the first nine months of 2016, marking a 10 per cent growth compared to the same period last year, according to Malaysia’s leading automotive online magazine Paultan.org.

In 2015, when the local economy appeared to be slowing, Mercedes sold a total of 10,845 vehicles, a record increase of 56 per cent from 6,932 units in 2014.

[…]

Based on the sales data, slower economic growth was not affecting all segments of the country equally. While those in the lower income brackets are complaining of rising costs, their more well-off counterparts have been splurging.

”What it indicates is that while the low and middle income earners are experiencing fiscal constraints, it is business as usual for the higher income group,” Muhammed told Malay Mail Online in a phone interview.

Global trend

Putrajaya has so far shrugged off the idea. According to official statistics, the country’s Gini coefficient series shows a downward trend in household income inequality from 2004 to 2012, after which it falls off drastically — the Gini coefficient was 0.46 in 2004 and only dropped by 0.3 percentage point after eight years. But in 2014, it dropped to 0.40.

I find the final paragraph (especially the final sentence) in this excerpt as slightly confusing. After laying out the situation in 2015 and 2016, the article goes on talk about the 2014 Gini data, which might not describe 2015 and 2016 very well.

Confusing, because the Gini coefficient is a low-frequency data done, at the moment, every 2-3 years together with the household income survey. Not only that, it lags severely, published only after the survey was done months earlier: the 2014 data was released in June 2015 while the 2012 data was released in July 2013. You can see its low frequency in the chart below:[2]

In contrast, car sales statistics are high-frequency data available monthly.[3] 

High-frequency data do have a lot to say about the present time. But I feel it is unfair to cast aspersion on low-frequency data from all the way back by using more recent information (2015-2016 car sales) the way the article does. It is unfair because the two datasets describe two different points of time. They are not contemporaneous data and not comparable, at least in the way it is being done.

I am aware of the paper by Lee Hwok Aun and Muhammed Abdul Khalid which the Malay Mail article cites. But the paper utilizes car sales data that is contemporary to the Gini coefficients it uses (before that, I would like to say it is a shame that Lee had to leave University of Malaya because of the short-sighted government spending cuts). You can read the working paper here.

In contrast, the Malay Mail article is taking post-2014 car sales data to question a 2014 Gini coefficient.

So, I think the attack on the 2014 Gini coefficient from the Malay Mail angel might be overdone, and different from the Lee-Muhammad criticism. The 2014 coefficient is just unable to describe the 2015 and the 2016 situation, especially since the GST was introduced in April 2015. There was a significant structural break since the 2014 coefficient was released.

[Also, I feel it is important to note that the Gini we have here measures income inequality, not consumption inequality. We have the Household Expenditure Survey though. Just saying]

In any case, the next Gini coefficient may come out this year or the next. The Household Income Survey is supposed to be done twice in five years (last done in 2014). The latest coefficient may yet go up.

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[1] — Syed Jaymal Zahiid. What BMW and Perodua sales data says about the economy. Malay Mail. January 21 2017.

[2] — 2014 Household Income Survey. Department of Statistics. Accessed Jan 23 2017.

[3] — Malaysian Automotive Association. Accessed Jan 23 2017.

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p/s — I am not defending the Gini coefficient per se. I am saying the criticism mounted in that particular way is off the mark.