Input-Output Analysis - Science topic

Dear Geoffrey,

Here are my two cents:

1. In both Leontief and Ghosh models the output vector is the endogenous variable, not final demand nor value-added.

2. In Leontief 's model, the exogenous variable is final demand and it is assumed that supply (labor, natural resources, etc.) constrains will not bind to any level of final demand. On the other hand, in Ghosh's model, the exogenous variable is value added (quantities or factor prices) and it is assumed that demand adjusts to any supply level.

3. The parameters differ as well in both models: in Leontief's model it is assumed that input requirements are proportional to output levels whereas in Ghosh's model it is assumed that sells of intermediate demand commodities are proportional to output levels.

With these elements, I think that more than ideology and independently of the other available models, it depends on the research question and what we think about the adequacy of the model to describe the economy: even though "resource[s] are increasingly scarce", are they binding constraints (given the research question) or more relevant than demand constraints? Which proportionality assumption makes more sense to the economy we are studying?

Best,

Daniel

If your analysis is time-history, the ALLPD output alonely satisfies your desire.

Dear Rozita Baba ,

Sincere enquiry: Isn't it that DEA a non-parametric method for analysing efficiency? Debora Addo 's questions seems to be looking for a software as opposed to a technique? Thank you -:

Dear Saad,

You have to use the model: ( [I-A]^-1)*Y'=X'. I include an exercise in Excel to do this as an example. I explained each step, in this case I changed final demand to get the new out at the end of the spreadsheet. You need to change your value added data for your purpose.

Hope it helps.

You can access IO Tables for Pakistan over the period of 2010-2017 from following link :

I suggest Matlab (suitable for matrix algebra) or Python (see http://www.real.illinois.edu/pyio/ and https://pymrio.readthedocs.io/en/latest/)

Aparna Sathya Murthy thanks, but what is its physical implication on circuit? whether it leads more to ground or more towards Vdd??

I think there are two recent discussions, the one between Dr. Flegg and Thomo defending their FLQi against the criticisms received in an article by Lehtonen and Tykkyläinen, I think the FLQi is still the best choice between "up-down" techniques for regionalization . On the other hand is the proposal of Asuad and Sánchez who contemplate the use of spatial correlations (Moran'I) for the estimation of sub-regional matrices and go in a "bottom-up" process, however, I think this proposal has two disadvantages when calculating weighting coefficients; a) the statistic I will always depend on the distance matrix that has been considered between two geographical spaces (cetroid distance of a polygon, road distance, and if so, the infrastructure is underestimated) and b) when using the RAS method, keep the problem of underestimating regional imports and overestimating multipliers.

Hello Samuel,

I came across following case study in International Journal of Productivity and Performance Management. (also available on researchgate)

Ian Cobbold, Gavin Lawrie and Khalil Issa (2004), ‘Designing a strategic management system using the third-generation balanced scorecard - A case study’, International Journal of Productivity and Performance Management Vol. 53 No. 7, 2004 pp 624-633

This may be useful.

Regards.

There is free software which will do this, as well as adjustment and filtering, for you.

Dear Lutz,

welcome,

Hope you are well!The input resistance of the differential transistor amplifier seen from the base of one transistor to the ground in the common mode can be expressed by

Ri = rbe + 2REE ( hfe +1), where rbe is the base to emitter small signal resistance, hfe is the small signal common emitter current gain of the transistor and REE is the common emitter resistance.

It is very large resistance.

The derivation is simple because of symmetry in the common mode one can split REE into two separate emitter resistances with every resistance equals 2REE. Then one has an input resistance looking from the base of each transistor as expressed previously.

If in the differential mode the input resistance from a base of the transistor to the ground is rbe and from base to base is 2rbe as the common emitter point will be at virtual ground.

Best wishes

Please have a look at the following link and PDF attachments.

Hi Brian,

The difference here is how the output gets used. For government, indeed parts of their output is used to produce other goods. Analysis on weather and soil is a services often produced by the government for the agriculture sector. This is often included as a "government" sector intermediate good in IO tables. However, much of government production is a "final good" in that it is not directly used in the production of another good. For example, a school is labor (teachers) and capital (buildings/land) combined with intermediate goods (various) to produce a final good - education. That education is a final good because is not used to produce any other goods during that time period.

Investment is considered a final good because it is not used for production until a new time period. For example, consider a tower being built in a city. The tower is built this year and then used next year. This year it is produced as a final good - it is not used in the production of anything else. Next year it is is added to the capital supply. It can now be used to produce more goods such as apartments (final good), or intermediate goods (such as office space). Hope this helps Kenneth

Dear Wasseem

Assuming a zero salvage value does not cause the asset to be overvalued. A zero salvage value (using straight-line depreciation method) does cause the annual depreciation to be the highest (assuming not reverting to market value based accounting midstream) and the asset value to be the lowest (i.e. potentially an undervalued asset). The instant you estimate the salvage value to be greater than zero than the annual depreciation expense declines and the asset value throughout the remaining life of the asset increases.

Hi Afridi,

I think you are mixing up two different terminologies. The under-actuation is something related to dynamics limitation while 'strict feedback form' is something more mathematical. These two are not related in any sense because the same actuating input may appear in multiple states or in other way one input might be integrated in several chains like a tree.

What is happening is that the CO2 is being sequestered. That is something we need in the real world to draw down CO2 from the atmosphere and reduce the greenhouse effect that is causing global warming,

OOps you added some problems. IVs are assumed to be measured without error. If they contain measurement error then you have an errors in variables model to consider. At this point, I would assume that there is no important measurement error and proceed as you suggest. I would then do the regressions with lasso to prevent multicollinearity and overfitting. After selection I would rerun the selected models in the usual programs to get the final prediction equations understanding that the prediction standard errors are at best approximate. I am not sure about running all of these models though. This seems like another multiple testing problem as in microarrays. These are usually treated by Bonferroni or Benjamin-Hochberg procdures. A beginning reference is at this link.

It seems that you have chosen a medically important but statistically difficult problem. If I can help you can always contact me through ResearchGate messages. Best wishes, David Booth

To all those who commented and gave reference, thank you very much. :)

Interesting models! I'm following

Then you should discuss with the Quantum ESPRESSO forum (http://www.quantum-espresso.org/forum/) or you may contact to the developers.

Hi Witold,

1. und 2. should be identical for a good fitting model, the second is based on an Bayesian approach (as far a I can see). 3. is an alternative method of assigning individuals to classes.

Here is some explanation that may be helpful for you:

Kind regards,

Karin

In order to maximize the number and the quality of the answers that you will get from RG and that will contribute to your project, my recommendation is including more details about the specification of the input-output matrix you wish to design, such as

I hope you will find these points useful for inspiring a fruitful thinking process.

Good luck!

Best wishes

Ilaria

 Hi Robert, 

Few years ago we tried to use input-output analysis as an approach to measure the economic impact of minning and compare in front of non-mining, communities in an arid zone in Mexico; following Rolfe and Ivanova (U. of Queensland) approach that they used in the Bowen Basin in Australia.

In our experience, we faced that the quality of the data available was far from desirable. Then we tried to built the input-output data... again the ammount and quality of data available make it a larger challenge than the project goals. Thus, we choose to mix some basic regional macroeconomic indicators, a survey and a stakeholders analysis, as an approach for measuring some economic and social impacts of minning in comparison with non-mining communities in the same region.  We exchanged the ellegance of the input-output analysis with a more detailed qualitative explanation of the econo-social perception about minning, in both kinds of communities. We published a book (in spanish) about that work last year..

 My suggestionn is to read Rolfe & ivanova's report about the Bowen Basin. Then compare the data available (quality, ammount, historic data, etc), checking the dissagregation level that they allow and, the ammount of assumptions and estimations that you were required to do to dissagregate those data available. If the data is far from that you require, be careful, could be a long nightmare.

Hoping that this cooment could be useful, 

Daniel

Not very accurate but in the absence of their non-availability  by statistical organisation of your country, they may be used. 

Is a big ingeniery  problems I suggest that  you can serparate this problem in many short problems using differents types of ingeniering enterprises

Dear Hamza

First you should determine you preferred DEA model. As you know, there are various types of DEA models with various applications and characteristics. There are fuzzy DEA models (FDEA), stochastic DEA models (SDEA) , ... . For now, you can use the conventional DEA models including CCR and BCC. i try to narrow down the steps as follows:

suppose you are going to rank 20 decision makin units (DMUs) which are projects by considering 3 factors, including, cost, income and time.

1. The first step is determining the input and output variables. input variables are smaller the better type (STB) such as cost and time while output variables are larger the better type (LTB) such income. so your conceptual model is composed of 2 input variables and one output variable.

2. now all you need is implementation of DEA model. MATLAB or GAMS are the best softwares for this purpose, although there are various independent sofwares in the market.

3. after determining the data, you can run the model and obtain the efficiency scores for projects and rank them accordingly.

there is one more thing to note. Conventional DEA models are two types, input oriented models and output oriented models. input oriented model tries to minimize the inputs while considering the outputs constant while output oriented models try to maximize the output while considering the inputs constant. so based on your research goal you have to determine which type to employ. i can send you MATLAB codes for BCC input and output oriented models along with CCR input and output oriented models for your convenience, all you need to do is determining your data in the code and run it.

Send an email to me so i can send the codes to you

i hope you find this useful

Use R, https://cran.r-project.org/web/packages/Benchmarking/Benchmarking.pdf

or

or

Please refer to the "Global Wage Report"

at

A well regulated source should not change its voltage one change in load. 

Dear Dor,

I have used many times WIOD database in my research. In order to derive A and L matrices if one row of total production vector x is equal to 0, I suggest to put a 1 in the corresponding element of the final demand vector. This way, the corresponding element in the total production vector will return 1, and the matrices A and L can be computed without affecting the values of the others economic sectors.

Moreover, for large multi-regional matrices such as the WIOT, I suggest to calculate matrix L using the Power Series approximation in a recursive way: L = (I-A)^(-1) = I + A + AA + AAA + ... . The stop criteria can be set as the equality between the total environmental impact (sum of the elements in the environmental intervention vector B) and the sum of the embodied environmental impact in final demand products (E = B*L), since the environmental impact is conserved.

I hope this may contribute in answering your question.

Regards,

Matteo Rocco

Dear Yoshinori and Lall,

 Yes, Shibata was a unique Scholar that was grown up in Kyoto under the influence of two big names, Hajime Kawakami (Marxist) and Yasuma Takata (Marx-critic). When I was affiliated with Kyoto University, I was entrusted by the daughter of Shibata (Junko Nagasaka) to select important books and materials from Shibata's private collections to preseve them in the University library. (It contains letters from Schumpeter, his reflection on war just after Japan's surrender, and obituaries in his funeral. But, from the eyes of a bibliographer, it is far from rich as economics library, since Shibata had to sell almost all of his Collection in the years of distress under the purge, )

   I dealt with Shibata's engagement in the wartime totalitarian reforms in "Economic Reform Plans in the Japanese Wartime Economy: The case of Shintaro Ryu and Kei Shibata", in Aiko Ikeo ed., Economic Development in Twentieth Century East Asia, Routledge, 1997. (pp.100-115)

   Such a historical description of Shibata's career culminated in Kuniaki Makino, Shibata Kei: Shihonshugi no chokoku wo mezashite (toward overcoming of capitalism), Kyoto: Mineruva Shobo, 2015. 234p. (in Japanese)

  Theoretical economists  maintained their interest in Shibata's attempt to criticize Marxian economics as well as the economics orthodoxy then.

  Takashi Negishi (1995) "Boehm-Bawerk and Shibata on Power or Market," Journal of Economics (Zeitschrift fuer Nationaloekonomie), 61(1), 281-299

.   Tadasu Matsuo (2010) "Average Period of Production in Circulating Input-Output Structure", Applied Mathematical Science 4(46), 2293-313.

   Dong-Min-Rieu (2009) "The Shibata-Okishio Connection: Labor Theory of Value and Rate of Profit", Journal of the History of Economic Thought, 31 (3) September 2009, pp. 325-339     

   In Japanese Atsushi Nishi published two articles under the influence of Matsuo (2010)  :

   Nishi, A. (2013) "On the Relation between the autoregressive pattern of input-output structure and the concept of average period of production: Shibata Kei's approch and Matsuo Tadasu's approach", Kikan Keizairiron 50(2), pp.89-76.

  Nishi, A. (2014) "On the Generalization of the Concept of Boem-Bawerk's Average Period of production to the Autoregressive Pattern of Input-Output Structure: Kei Shibata's Approach", Keizaigakushi Kenkyu 56(1), pp.48-70.  

   Bests!

Dear Bui Trihnh,

I uploaded a wrong version of my paper. Some of figures were broken. I have replaced it with the new PDF and renewed the link. I think now you can see figures in a good state. 

Thank you, Piero Esposito. I'm not sure neither, but I think that your answer is the best I saw until now.

Greetings from Brazil,

Marcelo

simple by using inta and intr and plz refer rafeeqzuman 80086/8088 book

You must know frequency (or pulse width, as you call it) limits your circuit will be operational. Circuits don't work well under signal frequency outside of their intended range.

Typically you'd want to test your circuit for multiple transition (rise and fall) times. If I were to pick one, I pick 50%. For three I'd pick 5%, 50%, 100% and so on to cover the entire frequency range.

This topic is covered in details at paripath.com and in the book amzn.to/1N66Hds.

Thank you to both for your contributions. We already have I-O tables corresponding to 2012 year.  What we would like to calculate is the impact over different activities of the expenditure done in farmers' markets in an aggregated way. Creating subregions would force us to calculate specific coeficients for the subregions, which we do not consider necessary. In summary, we would like to know the impact over regional GDP of marginal euros expended by consumers in local farmers' markets. 

First of all, Dear Iman, you must understand that  the so called SISO / MIMO, linear / nonlinear, time invariant/time varying   systems are only mathematical models of real systems. While developing the models  system analyst  make several assumptions  which may or may not be justified. The simplest models are obviously SISO  LTIV systems  which are crude approximations. Many man-made engineering systems are reasonably well approximated  within the ranges of operation by SISO LTIV models.. But in reality there some inputs which are ignored ( disturbances or noise) if they have little effect on the performance or can be ignored. Similarly linearity is always true within ranges. Time variation may be too slow so that it can be ignored. Again time delay is also possible. So, while modelling a real system, we start with the realistic. simplest (LTIV) and progressively move LTV, NLTIV, NLTV etc if the results are not . Another factor is the uncertainty which may require stochastic analysis.  Moreover, there is no model that will suit all situations , so we have to choose the better one from several models. Modelling even now is more of an art than science coming to modelling of real systems. I hope  I have not confused you. It s a matter of finding the best cap that will fit into a real hed. Good luck in your modelling studies.

Thank you Jonas, I have updated the question for disambiguation purposes and I shall take a look on resampling techniques.

Dear Oliver, we have developed a statistical model for measuring impact (MEMI) is giving us very good results. This is based on the combined use of multivariate techniques. you may wish to consult published by our magazine (Cuban Journal of Agricultural Science). For more details you can write to my personal email: rcobo@ica.co.cu

I take this contact to invite him to participate in meetings of biostatistics, econometrics and computing the V International Congress on Animal Production to be held in the Palace of Conventions in Havana, Cuba from 16 to 20 November this year. in this event some related multivariate statistics I see is your line of work papers will be presented. Please, if you are interested in this event, you can write to my email for sending all the necessary information. I hope that motivates and we can meet in Cuba. Best regards

Dr. C. Raul Cobo Wedge

Researcher, ICA

Hello Raj,

    The first question to ask yourself is if you want to evaluate the overhead analytically or empirically. If you want to do an analytical evaluation then just look at the specification for Java RMI and RPC over DDS -- BTW notice that RTI-DDS is a DDS implementation not the Standard, you may also consider some more widely used and Open Source alternatives as OpenSplice (http://www.prismtech.com/dds-community).

If you are looking to do an empirical analysis then you can somehow estimate the temporal overhead performing some basic tests for small sample. The space overhead can be estimated indirectly by looking at the throughout delivered to the application vs. the bandwidth used on the network. In that case recall to take into account he protocol headers for level 4 and level 3, e.g. UDP + IP or TCP + IP.

HTH.

A+

Dear Kumar, you can generate a script using macro manager ( actually it will generate a code in python while you create your model then you can put in a ,,for'' loop to modify the models as you want and automatically create other models based on the first one but with the variations that you want). 

Considering the Gibbs-Shannon entropy S, we know that

dS=-∑(lnp_i)dp_i

We will consider i=1,2,...,n with n>2. Then there are n-1 independent variations dpi.

You cannot uniquely determine n-1>1 independent quantities dp_i from a single quantity dS.

I am not sure if this is what you were asking?

To Massimo's sensible comment I would add that:

1) constructing I/O tables for small regions is very difficult. Usually they are estimated with some proportional rescaling of tables referring to wider areas (nations, etc.), so that the reliability of such data is very poor.

2) when the region considered becomes smaller and smaller (as in the case of a small township), its economy becomes more and more "open", in the sense of depending on exchanges with the "rest of the world". As a result, its sustainability is more a matter of what happens outside than inside the concerned region..

The quality factor Q is defined for reactive elements to show how far they are unlossy especially when they are built in a resonance circuit. If the reactance of the reactive element is X and its equivalent series resistance is rs, then its Q= X/ rs.  If the equivalent Resistance is in parallel and =rp, then the Q= rp/ X.

In case of series resonance circuit which is composed of LCR in series, at resonance 

XC= XL and the circuit Q= XL/ R=XC/R with R is the sum of all the resistances in series XL is the total inductive reactance and XC is the total capacitive reactance at reonance.,i.e., w=wo.

Your input circuit is equivalent to a series resonance circuit with a total equivalent series Resistance R= Rs+ gm LS/ Ct, where the second term gm LS/Ct is the equivalent input resistance between the gate and ground. Ct is equivalent total capacitance in series with Lg. Simple circuit analysis will show that your capacitance Ct is  equal to Cgs. The total inductance will be = Lg+ Ls. So,according to the formula of Q,

Q= XC/R = 1/  [Rs+ gm LS/ Ct] wo Ct as XC= 1/wo Ct.

For the condition of matching Rs= gm LS/ Ct, then we get Q= 1/ 2 Rs Ct wo,

Ct =Cgs . The resonance frequency WO= sq root of 1/ [Lg+ Ls] Cgs. Then you can calculate it knowing the parameters.

This may shed some light on the answer of your question.

There was an special issue in Economic Systems Research this year addressing that topic. I leave the link below in case it it of any use.

I find the book by Ronald E. Miller and Peter D. Blair "Input-Output Analysis: Foundations and Extensions," Prentice Hall, Inc 1985 very good in its coverage and examples. Its not time yet to forget the classical introduction by Robert Dorfman, Paul Samuelson, and Robert Solow, "Linear Programming and Economic Analysis," MacGraw Hill, 1968. Although William Baumol's  "Economic Theory and Operations Analysis," Prentice Hall 1961 is an old book, it is precious and basic for this topic as well.

thank u so much ...

Hi Haider Al-Ani, it is Particle Image Velocimetry.

what you see is the consensus sequence ... low coverage bases or low mapping quality bases tend to be represented in the lower case and places where there was no coverage may have n's ... which version of samtools are you using?

It depends on the sector you are studying...the approach I use for construction materials or buildings is product LCA

Have a look at my paper:

F. Asdrubali, C. Baldassarri, V.Fthenakis: “Life Cycle Analysis in the construction sector: guiding the optimization of conventional Italian buildings”, Energy and Buildings, 64 (2013), 73-89.

You can download it from Research gate

About data:

There is a 1991 SAM for Zimbabwe:

GTAP has SAMs for a few other South African countries: https://www.gtap.agecon.purdue.edu/

The EORA database also reports tables for Zimbabwe (but to be honest I think the data is unreliable):

About research questions:

To find inspiration maybe you can browse the literature on African economics (e.g., http://jae.oxfordjournals.org/). Possible questions: the effect of market distortions such as energy and food subsidies; the effect of climate change; the effect of international aid; etc... People like Sherman Robinson and Channing Arndt have interesting studies about Mozambique, South Africa and other African countries. Specifically about Zimbabwe a quick Google search returned:

http://repository.up.ac.za/handle/2263/3651.

I hope this helps.

First, you should find the differences between the original example code and yours. Then, check your code step by step. Meanwhile, GAMS shows the lines which have mistakes.

If it does not work, let me know.

The best way is sending your code to the RG-groups in order to get the best result.

Regards,

Morteza

Dear Martin, thanks for you advice. I know the article which has been derived from one of the PREM projects. At the same time, I was involved in three other PREM projects. Usually, CGE models make use of subst. elasticities (I've done it myself together with Reyer, one of your co-authors). The background of my question is my interest in the empirical analysis to derive substitution elasticities. Anyhow, I'll reread the article and thanks for your suggestion. Vincent