It’s been nearly a year since Malaysia’s minimum wage law came into effect. Although enforcement has been held off until next year from the loads of companies applying for a postponement, most have already complied.
So here’s my crack at trying to figure out what the minimum wage’s impact on Malaysian employment, unemployment and incomes. Most of this material is taken from a presentation I gave at UTAR earlier this week.
As always in such matters, the answer is: it depends (excerpt; emphasis added):
Should Policy Makers in Emerging Markets be Concerned about “Tapering”?
The US and European economies are showing some signs of recovery from the global financial crisis that began in 2008. As a result, the US Federal Reserve Bank is considering phasing out, or “tapering”, the extraordinary monetary policy measures through which it responded to the crisis…The World Bank's East Asia and Pacific regional update estimated that in East Asia alone $24 billion was withdrawn from equities and $35.2 billion from bonds...Financial markets largely recovered once the Fed decided to postpone tapering in September, but there is still nervousness….
October consumer prices accelerated slightly in October (log annual and monthly changes; 2000=100):
I did a series of posts along these lines ages ago, but as an overall summary, the following post from David Giles covers much the same ground and then some (excerpt):
Forecasting from a Regression Model
There are several reasons why we estimate regression models, one of them being to generate forecasts of the dependent variable. I'm certainly not saying that this is the most important or the most interesting use of such models. Personally, I don't think this is the case.
So, why is this post about forecasting? Well, a few comments and questions that I've had from readers of this blog suggest to me that not all students of econometrics are completely clear about certain issues when it comes to using regression models for forecasting.
Let's see if we can clarify some terms that are used in this context, and in the process clear up any misunderstandings…
There are a couple of concepts in this post that I never got around to covering (cointegration and order of integration), and I prefer as a rule to use lags anyway, but this is a pretty good primer on the mechanics of forecasting.
My friend Lars tried an experiment last week:
The Crowd: “Lars, you are fat!”
On Friday I was doing a presentation on the global economy (yes, yes mainly on global monetary policy) for 40-50 colleagues who are working as investment advisors in the Danske Bank group.
As I was about to start my presentation somebody said “The audience have been kind of quiet today”. I thought that was a challenge so I immediately so I jumped on top of a table. That woke up the crowd.
I asked the audience to guess my weight. They all wrote their guesses on a piece of paper. All the guesses were collected and an average guess – the “consensus forecast” – was calculated, while I continued my presentation…
I’ve done something of the same sort in some of the classes I used to run. It’s a great way to get audience participation, and to illustrate abstract economic concepts in real world settings. But Lars’ attempt was a lot funnier than mine. While I won’t hold this as proof positive that the efficient market hypothesis is valid under all circumstances, there is more than a grain of truth in it.
Well, it’s a week late, but better late than never.
GDP growth in 3Q2013 rose 5% on the year (log annual changes; 2005=100):
There’s been a dearth of posts on this blog for the past couple of weeks, mainly for two reasons: first, I had some deadlines to meet last week, and second, I took my year end holiday a little early – four days exploring the Forbidden City and climbing the Great Wall of China, among other things. No email, no twitter, no calls from the office…bliss.
Now its back to covering the Malaysian economy, though things will be a little slow as I catch up on data releases, news developments and the backlog of messages and posted comments. My view of 3Q2013 GDP should be out tomorrow (it was released last Friday), but first up is something a little easier to look at.
The September numbers aren’t nearly as pretty as the improvement in external trade (log annual and monthly changes; seasonally adjusted; 2000=100):
The momentum established from August has so far been kept up, which I hadn’t expected. There’s usually a lull after major holidays, so count this one as another pleasant surprise (log annual and monthly changes; seasonally adjusted):
Beating out August’s sharply higher numbers was never on the cards, so a pullback in growth was more or less what I thought might happen. But 4.7% in log terms was more than I hoped for.
Breaking it down:
Electrical and electronics shipments continued to grow, while there was a slight fall back in other exports, largely due to weaker refined petroleum products and metal manufactures. Crude oil jumped by nearly RM1 billion though.
Imports stayed – in my eyes anyway – more or less flat (RM millions):
October’s usually the boom month, where shipments go up to cater for the year end holidays in advanced economies, so if we’re seeing a true recovery in global trade, I’d expect to see even better growth for October.
Technical Notes:
September 2013 External Trade report from MATRADE
The outcome of yesterday’s Monetary Policy Committee was as predictable as the day – which is of course, a good thing. If things were actually interesting, something bad would have been happening (excerpt):
At the Monetary Policy Committee (MPC) meeting today, Bank Negara Malaysia decided to maintain the Overnight Policy Rate (OPR) at 3.00 percent.
The global economy continues to improve at a moderate pace…Looking ahead, there remain considerable risks that could affect the pace of the global recovery.
In the Malaysian economy, the expansion in domestic activity was supported by improvements in exports…Going forward, the growth momentum will benefit from the expected improvement in the external sector amid some moderation in domestic demand. Domestic investment activity will however continue, led by private sector capital spending and the ongoing implementation of infrastructure projects. Domestic demand is expected to moderate, reflecting the public sector consolidation and some moderation in private consumption. Uncertainties in the global environment may also affect the overall growth momentum.
For those who are interested in the rather refined job market for economists, this is a must read. From the email that announced the report:
New Report shows Job Market Trends for Economics & Finance Professionals
European Economists earn 30% less than Americans, worldwide even greater discrepancies.
INOMICS, an economics and finance recruitment network, on Wednesday, November 6, 2013 releases a worldwide overview of the economics job market. The Report is based on a survey between April and June 2013, in which 2,380 professionals and recruiters in the academic job market for economists answered questions about salaries, international professional mobility, the value of different levels of academic degree, and other issues related to economics and finance careers.
It turns out direct investment abroad isn’t exactly a zero sum game (excerpt):
Do multinationals that expand abroad invest less at home?
Theodore H. Moran, Lindsay Oldenski, 31 October 2013There is a long history of politicians accusing US MNCs of “shipping jobs overseas” when they invest outside the US…This line of attack implicitly assumes that expansion abroad by US firms substitutes for domestic expansion, harming US workers. It is equally possible that foreign expansion increases the productivity and market share of firms in a way that benefits US workers….
Keeping to the theme from last week, there’s a new paper on house price booms in the latest NBER working paper roundup (abstract):
What Explains House Price Booms?: History and Empirical Evidence
Michael D. Bordo, John Landon-LaneIn this paper we investigate the relationship between loose monetary policy, low inflation, and easy bank credit with house price booms. Using a panel of 11 OECD countries from 1920 to 2011 we estimate a panel VAR in order to identify shocks that can be interpreted as loose monetary policy shocks, low inflation shocks, bank credit shocks and house price shocks. We show that loose monetary policy played an important role in housing booms along with the other shocks. We show that during boom periods there is a heightened impact of all three “policy” shocks with the bank credit shock playing an important role. However, when we look at individual house price boom episodes the cause of the price boom is not so clear. The evidence suggests that the house price boom that occurred in the US during the 1990s and 2000s was not due to easy bank credit. Loose monetary policy (as well as low inflation) played some role but the residual which may be picking up other factors such as financial innovation and the shadow banking system is the most important shock. This result is robust to many alternative specifications.
How can you tell you’re in an asset bubble? How can anyone not look at this graph and say that we’re not (index numbers; 2000=100):
But I couldn’t and still can’t, at least not by any objective measure. Here’s a look at why.
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