Prof. Melvin Hinich passed away seven months ago on Sept 7, 2010 (click here for my first post). I lost a great mentor whom I can always refer to whenever I have any questions on mathematics/statistics/econometrics. I have kept most of our email correspondences, all with his classic Hinich sign-off: “Be well, Mel”.

In memoriam of Melvin Hinich, Ordershook et al. (2011) and Munger et al. (2011) summarized Mel’s path-breaking contributions to academia over the past four decades (to download the papers, click here and here). Though Mel achieved international reputation in four academic disciplines (economics, engineering, political science and statistics), he will be most remembered for his seminal contributions to the use of spatial anaysis in analyzing politics and public policy. Because of that, as highlighted by the above two papers, spatial voting choice theory occupies a central role in political science just as how fundamental consumer choice is to economics.

It is indeed a great honour for me to work with such a reputable scholar, who has made a huge impact in academia. In my eight years of collaboration with Mel, I can bear testimony to the descriptions in Ordershook et al. (2011: 1) and Munger et al. (2011:160):

“… with an endless energy for work and a childlike curiosity about the science of almost everything. Hinich’s scholarship blended technical virtuosity, theoretical depth, interdisciplinary sweep, and a keen eye for the main chance in terms of substantive importance. But Mel was not simply a bright but easily distracted scholar with many interests. Rather, he was a scientist, a scholar who found most problems interesting, and he was capable of making connections across fields because so many problems share a deep logical and mathematical structure.”

In time series analysis, Mel advocated the importance of identifying nonlinear serial dependencies. According to Hinich and Patterson (1985), many early investigators implicitly assume the observed time series is generated from a Gaussian process and test for white noise using the correlation structure, hence ignoring possible nonlinear relationships between consecutive price changes. From a statistical perspective, the distinction between white noise and pure white noise is nontrivial when nonlinear dependence is present. With that conviction, he developed nonlinearity tests using the bispectrum (Hinich, 1982), and later extended to the next polyspectral measure, the trispectrum (Dalle Molle and Hinich, 1995). To complement the frequency-domain, Mel has contributed the time-domain counterparts in bicorrelation test (Hinich, 1996), cross-bicorrelation test (Brooks and Hinich, 1999), and tricorrelation test (Wild et al., 2010). With the development of powerful statistical tools, the literature witnessed a surge of empirical evidence supporting the presence of nonlinearity in stock market data, with Hinich and Patterson (1985) the first one (see the extensive literature survey by Lim and Brooks, 2011).

The existence of nonlinearity calls into question the adequacy of linear models, and hence invites the development of non-linear time series models which are expected to provide superior forecasts than their linear counterparts or the naïve random walk. However, the evidence to date on the out-of-sample forecasting performance of non-linear time series models is still unconvincing. The title of Ramsey (1996) rightly pointed out the implication: “If nonlinear models cannot forecast, what use are they?” As typical of Mel’s character, he did not see the development of statistical tests as an endpoint, but how useful they are in explaining real world phenomena. Mel argued that the inability of researchers to make meaningful point forecasts of stock returns despite strong evidence of nonlinearity is caused by the episodic transient nature of such dependencies. His conjecture received wide empirical support across different financial markets. In fact, there is now a growing literature on time-varying predictability, with its theoretical foundation in the Adaptive Markets Hypothesis (see again the extensive literature survey by Lim and Brooks, 2011).

At the age of 71 years old, Mel still had an endless energy for research. As documented by Munger et al. (2011: 164): “On the day before he died, Mel talked with Bob Molyneux about their next visit and called up Munger to talk about a new chapter for the revised edition of Analytical Politics”. In fact, a few weeks before he died, he worked with his collaborators in Italy, Australia and Chile. His passion for research will always be my learning model.

It is indeed encouraging to learn that numerous research awards have been created by Malaysian universities to reward their staffs for research excellence (click here for a sample). One of those categories is the Young Researcher Award, which serves to encourage and reward excellence in research by young researchers or early career researchers. As an academic with immense curiosity, I was wondering how academia defines ‘youth’.

To satisfy my curiosity, I just do a quick Google search. The relevant results are summarized as follows:

1. Monash University, the Vice-Chancellor’s Award for Excellence in Research by Early Career Researchers: An ECR is someone who has had a PhD awarded (or equivalent research qualification/experience) within ten years of the date of application (click here).
2. National University of Singapore, Young Researcher Award: A young researcher is someone who is below 40 years of age at the time of application (click here).
3. Scopus Young Researcher Award: The award is open to those 40 years of age or less at the time of application (click here).
4. Prosper.Net-Scopus Young Scientist Award: Candidates should be less than 40 years old at the time of application (click here).

There are also a number of distinguished awards in academia that are open to those 40 years of age or less, though they are not explicitly labeled as Young Researcher Award:

1. Moran Medal: The Moran Medal in Statistical Sciences is awarded every two years by the Australian Academy of Science to recognize outstanding research by Australian scientists under 40 years of age in the fields of applied probability, biometrics, mathematical genetics, psychometrics, and statistics (click here).
2. Fields Medal: Its purpose is to give recognition to young mathematicians under the age of 40 (click here).
3. John Bates Clark Medal: It is awarded to American economist under the age of 40 who has made significant contribution to economic thought and knowledge (click here).
4. Fischer Black Prize: Eligible scholars must either be below age 40, or under age 45 but not have been awarded a PhD (or equivalent) by age 35 (click here).

Some years ago, my buddy Tuck-Cheong Tang forwarded an interesting article by Faria (2003) on the classification of economists, which I would like to share here (click here for Prof. Faria’s profile). Briefly, when more emphasis is placed on the quantity of their publications, economists are classified as r-strategists. On the other hand, K-strategists are those who target top journals as the outlets for their research papers. In his simple model, the author shows that neither r– nor K-strategies can maximize the influence of an economist in the profession. Instead, economists are more likely to be successful if they are able to strike a balance between quantity and quality.

Of course, this paper assumes that academics often strive to maximize the success of their careers (either to be prolific or influential). From my general observation, this is a very strong assumption in Malaysian academia as a whole. For instance, when many Malaysian public universities set publication in quality journals as a key performance indicator (KPI), many academics felt that their comfort zones have been challenged (see their grumblings here and here). It is worth highlighting that quality here is defined as citation-indexed journals such as Scopus or ISI/WoS, but not those top-tier journals targeted by K-strategists.

Even with such a realistic KPI, many are still feeling the pressure. I assume that they have no problem with KPI per se as performance evaluation is common in every public or private organization. Before joining academia, I was told that publishing academic papers is part and parcel of academic life (see here), and professors are those who have achieved intellectual excellence and are widely regarded as the experts in their respective fields of study. Just like the advice given by Sanjiv Das to those prospective PhD students and academics, “If you “know” that you enjoy research and will love teaching, don’t mind working all the time, anytime, for small money but great personal satisfaction, then sign up now. But don’t do it because you think the lifestyle is great, or you believe some rosy picture of an academic in an ivory tower” (click here). So what is the big fuss now? (I am supportive of the stand stated here and here).

I can only assume that they have been misinformed about academic life. As this author suggested,  “To avoid having “dead wood” in academia, universities should also stringently screen potential lecturers at the interview emphasising their expected role once they are in the system. Those who think they cannot comply with the university requirements can seek their fortune elsewhere” (click here).

Cuepacs, the umbrella union for civil servants, has been urging the government to abolish the Competence Level Assessment (PTK) for many years (for the latest, see here).

In academia, regardless of whether it is a public or private university, the competence of a lecturer should be evaluated based on his/her teaching performance and research achievements, with the latter getting a larger weight. In Malaysian public universities, PTK is a compulsory requirement for promotion exercises. For instance, PTK 3 is required for promotion to Senior Lecturer, whereas applicant for Associate Professor must have passed PTK 5. I always hold the view that academics should be promoted primarily on the basis of their research achievements. If pure scholarly merit and intellectual excellence are not the basis of promotion, then one would be left with the question of what do professors profess (see the article by Orr, 2000).

I am glad that our Prime Minister Datuk Seri Najib Tun Razak, in his 2011 Budget speech on 15 October 2010, announced that the PTK for civil servants has been abolished and will be replaced with a more suitable evaluation system by June 2011 (see here). According to a news report, when the Prime Minister highlighted this at the national teachers’ assembly at Stadium Putra, it drew thunderous applause from the audience (see here).

I am deeply saddened by the news that Prof. Melvin Hinich has passed away on Sept 6, 2010 (click here). It is really touching to read through the sharing of those he has influenced either as a researcher, mentor, teacher, or friend (see here). At this moment, I find it difficult to use the right words to describe my sadness.

Mel is a world class scholar whose publications traverse four fields: the spatial theory of voting in political science, time series analysis in statistics, political economy and regulatory issues in economics, statistical theory and methods in engineering (you may read his Wikipedia entry here).

Mel was a great mentor and teacher. When I worked on my master thesis in 2002, I saw the potential of his bispectrum test in addressing the research question. However, I did not have the skills to write the computer code.  I was then trying my luck to see if Mel could share his code. Unexpectedly, given his busy schedule, he responded my email and attached his FORTRAN code. He even invited me to meet up during his visiting trip to Singapore the following month. I was in a state of disbelief that a world class professor would meet up with a master student from a Malaysian university. Without much hesitation, I grabbed this rare opportunity and took a train from Kuala Lumpur to Singapore. We didn’t talk much in that short meeting, as I was in awe of his reputation. But he was patience enough to demonstrate the execution his bispectrum test.

After coming back from Singapore, I wrapped up my master thesis within the next 2 weeks. During the viva voce, the examiner has very few comments, and the thesis was granted a pass with minor corrections. I subsequently extracted a paper from the thesis, and invited Mel to be the third author (my supervisor M. Azali was the second author). He promptly responded with a ‘yes’, and told me that he liked the paper very much. Unfortunately, the three referee reports from Macroeconomic Dynamics suggested major revisions, and eventually we did not resubmit. Mel still kept a copy of this working paper in his website (click here). Despite the setback, this first collaboration has given me the much needed confidence to kick start my academic career.

I have known Mel for 8 years, and it is impossible to share those wonderful moments in this short posting. As I walk down the memory lane, I will compose some thoughts in his loving memory. He has been an inspiration and role model to me, and no word can describe my gratitude to him.

By Kian Ping