Questions related to Input-Output Analysis
While Leontief's system makes the driving demand force (consumption) endogenous, Ghosh's system makes the driving supply force (value-added) endogenous (Guerra & Sancho, 2010). In a context wehere resource are increasingly scarce, can anyone explain me why would we consider Ghosh's system outdated (aside from the argument that traditional markets dead end work as per Leontief's system)?
I know that R Software specifically Benchmarking package can be used to assess the MEA scores but I don't know how to capture the non-discretionary inputs when running a non-oriented analysis.
I have a standard input-output model. I have calculated the technical co-efficient and Leontief inverse for it. The problem that I am facing is : How can i change the value of value added and still run the model. What will the new final demand be in this case? Let me give an example of what I am talking about.
A B Final Demand Output
A 40 70 40 150
B 30 20 50 100
VA 20 35
Lets say VA (Value Added) increased for B by 5. How would I calculate the new final demand to find the new output. What is new final demand in this case?
Hi, I wish to use a macroeconomic model to analyze the environmental and social-economic effects of biofuel quotas in two countries. For environmental assessment, I am considering the carbon footprint and biodiversity losses. And for the latter, I want to look into income inequality.
In your opinion, what are the advantages and disadvantages of using E3ME and environmentally extended input-output method to do this task? Or do you recommend other models for this task?
Thank you in advance.
I crave your suggestions on the best analytical software for analyzing economic impact using input-output and multiplier analysis?
Which of these is most appropriate: Stata, EViews R, SPSS or SAS...or any other?
I welcome constructive suggestions.
Kind regards and stay safe 🙏
In many CMOS circuits i have seen Floating inputs implementation. how do we practically implement the same?
Beyond, how do floating input behave in a digital mechanism? A logic "low" or logic "high"?
Given the somewhat old techniques to obtain regional input ouput matrices by hybrid methods such as the popular RAS method or the implementation of location quotiens, in your opinion, what are the methods that offer a more accurate estimation of input output tables? What do you think are recent promising methods to undertake this task?
As part of my bachelor thesis, I am currently reading the literature on performance measurement, since I would like to implement such a system in our start-up initiative. Can anyone recommend me a book/paper which shows the introduction of an Input-Process-Output-Outcome system or the Balance Scorecard at a real example in practice?
That would help me so much !! Thank you !
Let me briefly go through the problem I am facing.
Currently, I have data ( of ground acceleration) obtained from the "seismic accelerograph instrument system" which was placed at the basement of the building and the plot is shown below. According to the plot, it is showing a random waveform up to a certain time and it starts decaying (damping occurs). However, it again gets another waveform (sinusoidal, as shown in the figure) after 300 sec. It looks very unusual to me. I suspect the sinusoidal part to be a building response. But I couldn't decide whether my assumption is valid or not.
So, my questions are:
- Is there anything (books/journals/published or unpublished thesis/lecture notes) that talks about the limitations of the time period which we are supposed to make while plotting the ground motion data?
- Is there any specific guidelines or any thumb-rule to determine whether the certain waveform is coming from the earthquake motion or is a building response? Normally, what I do is- I consider the random waveform as an "earthquake response" and a sinusoidal waveform as a "building response". Is it the correct way or is there another way we need to look at?
- My confusion arises when I saw a portion of "sinusoidal" wave before there is damping. In the figure, it is shown under the "orange" box. So, is it acceptable if I make a statement like- the presence of sinusoidal wave along with the random wave is due to the fact that the sensors recorded the both "earthquake and building response" at a time?
- If No, how can it be justified? If Yes, how do I correct this problem?
Thank you so much.
Simple question (back to basics):
For a classical diff. amplifier (Q1 and Q2, finite dynamic resistance re in the common emitter leg): How do we calculate the input resistance at the base of Q1 ?
As I understand it, each row (equation) in an input-output table represents the total output of an industry Xi and the entries in that row represent the amounts of Xi’s output used by all industries (including Xi itself) as well as "final demand." Final demand is typically disaggregated into consumption, investment, government, and exports. I find this confusing because “investment” and parts of “government” pertain to the supply side of the economy, so why are those portions of Xi’s output not included in the industrial entries listed in the equation prior to final demand?
When we only know about its current price in the market, life span & not knowing its original cost and salvage value.
When working with IO (Input-output) model for sectoral CO2 calculation sometimes you have negative 'changes in inventory' sometimes big enough to make total final demand for that sector negative. which will obviously undermine the actual CO2 emissions for that sector. if due to this negative changes in inventory we calculate a sectors total emissions to be negative for a particular year what would be the best interpretation for such a negative result?
I mean how can I present this kind of result?
or we can ignore changes in inventory when working with IO tables?
I would like to ask anyone with a good knowledge on confounding variables and IBM SPSS Statistics (23.0 or above) for Windows, how, in a sample with lots of input and output variables, the output variable predictions (test results) by the input variables of interest may be adjusted for other input variables that may very well confound with the test result.
Consider the following situation:
You have 95 primary input variables (input variables of interest)
- These 95 variables are all continuous variables.
You have 5 primary outcome variables (output variables of interest)
- 2 are continuous
- 2 are categorical with 2 categories
- 1 is categorical with more than 2 categories
You have identified 17 additional input variables, of which each one may or may not influence (interfere with any of the) primary (both input and output) variables.
- 4 are continuous
- 9 are categorical with 2 categories
- 4 are categorical with more than 2 categories
The research question is simple: determine the role the 95 primary input variables have in predicting the 5 primary outcome variables.
Potential problem: possible interference by any of the 17 "additional" input variables. Your ultimate goal is to get a test result that has been adjusted for the variables that have shown to significantly influence either input or output variables.
Let's set an example: you wish to assess the role (any of the) 95 variables (has) have in predicting one of the 2 continuous primary outcome variables. This may be done with Pearson's correlation coefficient, or with Spearman's rank correlation coefficient. The choice depends on the satisfaction of parametric testing prerequisites (most importantly: distribution of variable values statistically insignificantly differing from a Gaussian distribution; and homoscedasticity across the variable values).
You want to adjust the results of either Pearson or Spearman's test in SPSS for all of the 17 possibly confounding variables, that SPSS might identify as a significant confounder. How can this be achieved (easily) in SPSS?
Thank you very much in advance.
I propose a "common sense" built around a domain ontology knowledge of the activity of emergence fueled by the same conditions of validity and situated facts used in the input model to qualify a priori and ex-post exchange. This would be two distinct symbolic representation models.
When reporting from the Mplus output number of participants assigned to classes are we referring to?
1. FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THE ESTIMATED MODEL
2. FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON ESTIMATED POSTERIOR PROBABILITIES
3. FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP
Thank you for clarifying
I am looking for experience in using input-output matrix for analyzing supply chains from a bird's eye view. I plan to elaborate a regional input-output table from the national one and improve it by survey methods. Also, an extensive qualitative survey will be conducted to discover supply chains in details. Opinions, ideas, earlier experiences welcomed.
We started a new project to analyze supply chain resilience in New Zealand. The plan is using bottom-up collected quantitative and qualitative data as an addition to the already established statistical database, and use these for developing the network and input-output models. We want to model the ripple of effect of different events and explore the potential impacts improving the bouncing back capabilities. Do you have any similar experience in any parts of the above? I would like to talk about your experience and understand what kind of difficulties we have to face off.
Pakistan does not maintain input-output table. I find this source (http://worldmrio.com/country/), where the I/O tables of all countries are available. In addition, are these tables balanced?
How would you rate the accuracy of individual country based input-output tables available at http://worldmrio.com/country/? Are they balanced?. Available from:
I'm trying to create a multiple regression that explains the final price of electric energy in Brasil. Any suggests about which could be the independent variables?
Who has data on the wage bill of the sum of all sectors prior to 2008? They are no longer available from the statistical office. Thanks.
I'm using the WIOD database to compute GHG emissions embodied in imports to Israel. While calulating the a-matrix (technical coefficients) I have to decide how to handle total ouputs with 0 value, e.g. sector P: households with employees, at most regions. That is in order to prevent NAN values, an to ensure Leontief Inverse can be computed.
Currently I assigned a relatively small values to those cells, i.e. 0.00000000001 Million USD, but I was wondering if it is indeed the correct way to handle it, or should I apply zeros to NAN values in the tecnical coefficient matrix?
Michio Morishima liked to talk that three representative economists of pre-WWII Japan were Takata Yasuma (高田保馬, Y. Takata), Shibata Kei (柴田敬, K. Shibata) and Sono Shozo (園正造, S. Sono; mathematician). I do not believe this is an impartial estimate, because three of them were professors of Kyoto Imperial University (now Kyoto University) where Morishima himself once studied as a student and worked as a teaching staff. Even though, Shibata was one of a few economists whose contribution in theoretical economics gathered some light during the Inter War Period.
Shibata is most known by the fact that O. Lange (1934-35) cited his work (Shibata, 1933). P. Samuelson (1967) picked up this episode in commemoration of the centennial of the first volume of Marx's Capital.
However, Shibata has much more varied faces. Hiroshi Ohta tells about Shibata's connection to Leontief's input-output tables. He may have many more "unknown" contributions to economics. Please post any information about him. Your re-appraisal of Shibata's works is included among this information.
Lange, O. 1934−35 Marxian Economics and Modern Economic Theory, Review of Economic Studies 2: 189−201.
Samuelson, Paul A. 1967 Marxian Economics as Economics. American Economic Review 57(2): 616-623. Short comments in p.621 and p.622.
When we say "international" Input Outpu Table (IIOT), it comprises binational and multinational tables. I am more interested in multinational IOT.
I know that the IDE (now IDE-JETRO) published in 1976 a binational IIOT Japan-Korea 1970. IDE published in 1981 a multinational IIOT ASEAN Countries 1975. It published in 1992 the IIOT Asia 1985. Do these dates show the first publication and compilation years of International IOTs?
Why do OECD's Input-Output Tables (IOT) and Trade in Value Added (TiVA, that is derived form the former) give similar but different values for Value-Added (variable 'VALU')?
Which one should I use to perform a multi-country comparison?
IOT serves better to my intents, since it gives data for more years (every year from 1995 to 2011). TiVA has data only for 1995, 2000, 2005, 2008, 2009, 2010 and 2011.
Thank you all very much for your help.
Marcelo Scalabrin Müller
Some Articles assume 5% of the input signal’s pulse width as rise/fall time.
Is there a Specific Formula for that (especially for Cnfets)?
We are analysing the economic impact of local farmer's market in the Basque Country (Spain), adapting SEED methodology developed by Loyola University of New Orleans. Our region has updated the input-output data, but we would need to calculate the regional multiplier to estimate the impact of the markets over the regional economy.
I am looking for a practical system whose delay-free dynamics is BIBO stable. What about a real-world SARX system with small switching frequency?
When using availability in days as a single input and around 4 outputs (varying from 0 to 1), the efficient results seem odd. Although waiting for 1 or 2 days should be almost the same (in a large sample with up to 60 days of waiting time), DEA only selects DMUs that are immediatly available (i.e. 1 day) and disregard other DMUs that have higher values in outputs. Since assigning weights does not produce results (because the time values remain proportional), is there any sort of smoothing process that can better reflect our perception of time when using DEA?
I am trying to do an impact analysis using our own inter-regional input-output system for Austria. My first choice would be to do that in GAMS. a preexisting code for inter-regional I-O models would of course help a lot.
I am trying to find some performance parameters of middleware, so I want to calculate overhead on top of my original data size by middleware.
e.g., Data size = 8 bytes, sending 1000 times, will be = 8000 bytes, what will be overhead by middleware.
I have to run 500 odd simulations and I am only interested in few of the outputs at certain critical location. I am changing input files to model these models but now I have to run every simulation and then generate outputs in form of .rpt for each simulation in ABAQUS's GUI.
I would also interested to know if there is a way to read multiple .inp file one by one by writing a script.
Let's use an example. We have a function y = f(x), in which x is the input (the probability) and y is the output (the entropy). If we change y in y', can we find an x' such that f(x') = y'?
In other words, I know that when p changes, H changes; is it possible the opposite, such that if H changes, p changes?
As we know that quality factor "Q" is defined as follows,
Q= (Average energy stored)/ (energy loss/ second)
How do you obtain this quality factor for any input circuit?
I have shown in the below links,
1) First link shows the Quality Factor "Q" equation obtained for the second link diagram shown
2) Second link shows ,for this diagram, we need to obtain the quality factor for the input circuit
Can somebody give me an idea how to obtain the quality factor of our input circuit? Generally also, can you share how to obtain the quality factor of any circuit?
How can I simulate a critical path with input pattern (how can I know the input pattern which simulate the critical path and)?
Is industry linkage (based-on input-output analysis) a suitable choice? Or are there other better methods?
What are the basic books in input output analysis? What are the good books in input output analysis ? Is there any book which explains step by step of doing input output analysis? How can it be applied to public economics, in intergovernmental transfers?
I have 3 inputs to train the ANFIS. According to the model which i have proposed, one input of the current process is the output of last process.ie; one input depends on the last output. I have collected the real time training data which consists of only 2 inputs. How can i provide the third input, which is not part on my training data?
Can anyone help me.
Does anybody know how to create an output map of PIV where the graph has a gradient color map instead of colors arrows?
I am using bwa for the mapping of single end reads to the reference genome using following commands.
bwa-0.7.5a/bwa index -a bwtsw ref.fna
bwa aln ref.fna reads.fq > in.sai
bwa samse ref.fna in.sai reads.fq > out.sam
samtools view -S out.sam -b -o out.bam
samtools sort out.bam out.sorted.bam
bam2fastq -o reads.fq --no-aligned out.sorted.bam
samtools mpileup -uf ref.fna out.sorted.bam | bcftools view -cg - | vcfutils.pl vcf2fq > final.fastq
seqret -osformat fasta final.fastq -out2 final.fa
My final output file look like this nnnnnnnnnnncgctagTGACATATATATctaaaaaaaagctTTGCC.
In my final output file (final.fa), I found that there are a lot of lowercase bases and the fa file is a mixture of small n, upper case bases and lowercase bases! What is the actual meaning of lowercase bases present in the file? Do they relate to the quality of information? Should they be discarded or translated to upper case? Note: My reference genome (ref.fna) file does not contain any lowercase bases.
Life Cycle Assessment (LCA) is a widely used approach in environmental, economic, and social sustainability assessment of products or systems.
This will assist me in grasping and applying the concept of input-output models and social accounting matrices.
I am using and have modified a cross entropy balancing program code using GAMS for my social accounting matrix. In the program, if a cell has a value of zero, it should remain unchanged. However, I end up zeroing a cell value and generating another cell value where they are not really supposed to be. Could someone help me on this? I am willing to send the GAMS file. I got the file from http://www.gams.com/modlib/libhtml/cesam.htm and have modified its data set to fit to my research needs. I have also removed one row and one column from the original set file. Also, I have renamed some of my strings. The original program seems to work perfectly. I suspect that the altering the strings is the problem. However, I do not have enough knowledge in GAMS code programming to decipher and fix the problem.
I'm looking for parameters of water use in an applied general equilibrium model.